Circuit arrangement for reducing passband fluctuations of band-pass filter

Abstract

The invention provides a circuit device for reducing passband fluctuation of a band-pass filter, which relates to the technical field of band-pass filters and comprises a band-pass filter module, an output signal processing module, an element regulation and control module, a temperature control module and an element regulation and control module. The output signal processing module is used for calculating the passband fluctuation of the band-pass filter module and calculating the optimal capacitance value and the optimal inductance value during the optimal passband fluctuation; and the temperature control module is connected with the band-pass filter module and is used for detecting and adjusting the temperature of the element regulation and control module in real time. The sampling frequency is processed and optimized through the output signal processing module, the capacitance value and the inductance value in the band-pass filter module are adjusted through the element regulation and control module, and the self-adaptive capacity of the band-pass filter module is achieved; and the temperature control module detects and adjusts the temperature of the element regulation and control module in real time, so that the influence of the temperature on the band-pass filter module is reduced, and the passband fluctuation is further reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of band - pass filters, and particularly to a circuit device for reducing the pass - band ripple of a band - pass filter. Background Art

[0002] A band - pass filter is an important electronic circuit component, widely used in the field of signal processing. It allows signals within a specific frequency range to pass through while suppressing signals below and above this frequency range. A band - pass filter is usually composed of a high - pass filter and a low - pass filter combined. By adjusting the cut - off frequencies of these two filters, the pass - band range of the band - pass filter can be set.

[0003] Pass - band ripple is an important concept in filter design, which relates to the stability of the frequency response of the filter within the pass - band. Pass - band ripple may be caused by various factors, including imperfections of filter components, inaccuracies in circuit design, external interference, etc. These factors may lead to non - uniform frequency response of the filter within the pass - band. Reducing pass - band ripple is an important goal in circuit design, especially in filter design. Therefore, in circuit design, especially in high - frequency circuits and precision electronic devices, reducing pass - band ripple is crucial.

[0004] Components such as capacitors and inductors in existing band - pass filters do not have ideal characteristics. Their actual values change with temperature, frequency, and other factors, resulting in a difference between the filter response and the theoretical design; the values of capacitors and inductors change with temperature, leading to ripple within the pass - band of the filter. Summary of the Invention

[0005] The present invention provides a circuit device for reducing the pass - band ripple of a band - pass filter to solve the defect that components such as capacitors and inductors in existing band - pass filters do not have ideal characteristics. Their actual values change with temperature, frequency, and other factors, resulting in a difference between the filter response and the theoretical design; the values of capacitors and inductors change with temperature, leading to ripple within the pass - band of the filter.

[0006] On the one hand, the present invention provides a circuit device for reducing the pass - band ripple of a band - pass filter, including: a band - pass filter module, an output signal processing module, a component regulation module, and a temperature control module.

[0007] The band - pass filter module is used to receive frequency signals within a preset frequency range, convert the frequency signals into sampling frequencies, and simultaneously suppress signals outside the preset frequency range.

[0008] The output signal processing module is used to construct a capacitance and inductance optimization model based on the gradient descent method, and optimize the capacitance and inductance optimization model using the whale algorithm. The frequency response, initial capacitance value, and initial inductance value are input into the capacitance and inductance optimization model to obtain the optimal capacitance value and optimal inductance value.

[0009] The component regulation module is used to adjust the capacitance value and inductance value in the band-pass filter module according to the optimal capacitance value and optimal inductance value.

[0010] The temperature control module is used to detect and adjust the temperature of the component regulation module in real time.

[0011] According to the circuit device for reducing the passband ripple of the band-pass filter provided by the present invention, the output signal processing module includes a frequency receiving unit, a frequency response unit, and a matching unit.

[0012] The frequency receiving unit is used to receive the sampling frequency.

[0013] The frequency response unit is used to calculate the frequency response of the sampling frequency and establish a fluctuation set according to the frequency response.

[0014] The matching unit is used to calculate the fluctuation of the frequency response and calculate the optimal capacitance value and optimal inductance value required for the fluctuation to reach the minimum value.

[0015] According to the circuit device for reducing the passband ripple of the band-pass filter provided by the present invention, the formula for the frequency receiving unit to calculate the frequency response is expressed as:

[0016] In the formula, γ f is the frequency response value, L is the inductance, C is the capacitance, and f is the frequency.

[0017] According to the circuit device for reducing the passband ripple of the band-pass filter provided by the present invention, the steps for constructing the capacitance and inductance optimization model include: Establish a basic capacitance and inductance optimization model based on the gradient descent method.

[0018] Use the whale algorithm to optimize the learning rate of the gradient descent method.

[0019] Train the basic capacitance and inductance optimization model using the fluctuation set. Retain the model parameters that meet the preset accuracy to obtain the capacitance and inductance optimization model.

[0020] According to the circuit device for reducing the passband ripple of the band-pass filter provided by the present invention, the gradient descent method includes: Determine the loss function of the minimum passband ripple, and the formula is expressed as:

[0021] Wherein, F is the minimum passband ripple loss function, max(γ f ) is the maximum frequency response in the sampling frequency, and min(γ f ) is the minimum frequency response in the sampling frequency.

[0022] Calculate the gradients of the required capacitance value and the required inductance value, and perform iterative updates in combination with the gradients. The formula is expressed as:

[0023]

[0024] Wherein, L new is the gradient update value of the required inductance value, and C new is the gradient update value of the required capacitance value. and are the gradients of the required inductance value and the required capacitance value respectively, and α is the learning rate of gradient descent.

[0025] According to the circuit device for reducing the passband ripple of the band-pass filter provided by the present invention, the steps of optimizing the learning rate of the gradient descent method by using the whale algorithm include: Set the number of whale populations, the maximum number of iterations, and the upper and lower bounds of the search space.

[0026] Randomly generate a group of candidate whales as the initial population, and each whale corresponds to a group of learning rates.

[0027] Initialize the whale position in the search space as D.

[0028] Calculate the fitness of each whale. The formula is expressed as:

[0029] Wherein, D α is the fitness function, n is the population size, β is the whale individual, y β is the true value, is the predicted value.

[0030] Update the position of each whale according to the fitness by using the behavior of surrounding the prey and hunting.

[0031] Recalculate the fitness value for the updated whale positions, and update the current optimal solution according to the maximum fitness.

[0032] Repeat updating the positions of the whales until the maximum number of iterations is reached, and output the position of the whale with the highest fitness value as the optimal solution of the learning rate.

[0033] The circuit device for reducing the passband ripple of a band-pass filter provided by the present invention uses the calculation formula for updating the whale position by surrounding the prey, which is expressed as:

[0034] In the formula, H is the distance between the current whale and the prey in surrounding the prey, D * is the position of the current prey, D(t) is the position of the current whale, D(t + 1) is the position of the whale at iteration number t + 1, A and E are coefficient vectors, and t is the current iteration number.

[0035] The calculation formula for updating the whale position by using the hunting behavior is expressed as:

[0036] In the formula, H' is the distance between the current whale and the prey in the hunting behavior, i ∈ {0, 1}, e is the base of the natural logarithm, and b is a constant defining the spiral shape.

[0037] The circuit device for reducing the passband ripple of a band-pass filter provided by the present invention uses an adaptive PID control algorithm in the temperature control module to achieve temperature regulation of the temperature environment of the band-pass filter module. The formula is expressed as:

[0038] In the formula, u(t1) is the output value of the temperature at time step t1, K p is the proportional gain, K j is the integral gain, K d is the derivative gain, τ is the time constant, t1 is the time step, e(t1) is the temperature error, qτ is the differential representing the time constant τ, is the derivative of the temperature error e(t1) with respect to time t1.

[0039] The circuit device for reducing the passband ripple of a band-pass filter provided by the present invention uses the grey wolf algorithm in the temperature control module to optimize the proportional gain, integral gain, and derivative gain of the PID control algorithm. The formula is expressed as:

[0040] Traversing the fitness of each grey wolf is expressed as: when θ j < θ best then θ best = θ j and X best = X j .

[0041] In the formula, θ best is the optimal fitness, θ jThe fitness of gray wolf j, X j The candidate solution corresponding to the fitness of gray wolf j, X best Is the optimal solution corresponding to the gray wolf with the best fitness.

[0042] After the traversal is completed, the optimal solution is used as the optimal proportional gain, optimal integral gain, and optimal derivative gain required in the adaptive PID control algorithm.

[0043] According to the circuit device for reducing the passband ripple of a band-pass filter provided by the present invention, it further includes a frequency output module, and the frequency output module is used to receive the sampling frequency and display it through an oscilloscope built in the frequency output module.

[0044] The circuit device for reducing the passband ripple of a band-pass filter provided by the present invention combines the response frequency, optimizes the learning rate in the gradient descent algorithm model through the whale algorithm to find the optimal capacitance value and optimal inductance value under the minimum passband ripple, solves the problem of non-optimal matching between capacitance, inductance, and response frequency, and achieves the beneficial effect of realizing the optimal matching between capacitance, inductance, and frequency response and achieving the best noise reduction.

[0045] The circuit device for reducing the passband ripple of a band-pass filter provided by the invention realizes the temperature regulation of the temperature regulation unit by using an adaptive PID control algorithm, solves the influence of temperature on the band-pass filter module, and achieves the beneficial effects of adaptively regulating the temperature of the band-pass filter module, precisely controlling the temperature of the band-pass filter module, and improving the noise reduction efficiency and robustness of the module. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0047] Figure 1 It is a schematic structural diagram of the circuit device for reducing the passband ripple of a band-pass filter provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0048] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention with reference to the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present invention belong to the scope of protection of the present invention.

[0049] The following combines Figure 1 to describe the circuit device for reducing the passband ripple of a band-pass filter according to the present invention.

[0050] Figure 1 is a schematic structural diagram of the circuit device for reducing the passband ripple of a band-pass filter provided by an embodiment of the present invention.

[0051] As Figure 1 shown, the circuit device for reducing the passband ripple of a band-pass filter provided by an embodiment of the present invention includes: a band-pass filter module, an output signal processing module, an element regulation module, and a temperature control module.

[0052] Band-pass filter module: It is used to receive frequency signals within a preset frequency range, convert the frequency signals into a sampling frequency, and simultaneously suppress signals outside the preset frequency range. The key characteristics of a band-pass filter include the center frequency and the bandwidth. The center frequency is the frequency at which the filter response is the strongest, usually located at the midpoint of the filter passband. The bandwidth is the frequency range that the filter allows to pass through. The bandwidth can vary from a few tens of hertz to several kilohertz.

[0053] Output signal processing module: It is used to calculate the frequency response ripple of the sampling frequency to obtain the magnitude of the passband ripple of the band-pass filter module; calculate the optimal capacitance value and the optimal inductance value at the optimal passband ripple. The output signal processing module includes a frequency receiving unit, a frequency response unit, and a matching unit; the frequency receiving unit is used to receive the sampling frequency, the frequency response unit is used to calculate the frequency response of the sampling frequency, and establish a ripple set based on the frequency response. The frequency response is a characteristic that measures the response ability of a system or device to different frequency signals. In the passband, the ripple of the frequency response curve is sometimes called the ripple. The magnitude of the ripple can be described by the peak ripple (i.e., the maximum value of the gain fluctuation) and the peak-to-peak ripple (i.e., the maximum difference of the gain fluctuation). The peak ripple refers to the maximum amplitude of the voltage or current fluctuation. In one cycle, the amount from the average value to the maximum deviation is the peak ripple. It is usually used to measure the stability of the power supply output waveform. The peak-to-peak ripple refers to the entire range of the voltage or current fluctuation, that is, the difference from the maximum value to the minimum value in one cycle. The peak-to-peak ripple is a more comprehensive indicator for measuring the amplitude of the power supply output fluctuation. Both can directly reflect the change in the magnitude of the passband ripple. The matching unit is used to calculate the ripple of the frequency response and the optimal capacitance value and the optimal inductance value required under the minimum ripple The characteristics of the frequency response include: the frequency range that the system can handle; the amplification ability of the system to different frequency signals; the frequency at which the system gain drops to a certain ratio (usually half of the maximum gain, i.e., the -3dB point); in some systems (such as vibration systems), the gain peak appears at a specific frequency; the situation of the output signal phase changing with the frequency.

[0054] The formula for calculating the frequency response is expressed as:

[0055] Wherein, γ f is the frequency response value, L is the inductance, C is the capacitance, and f is the frequency.

[0056] Establish a fluctuation set of the frequency response in combination with the frequency response.

[0057] The specific steps for establishing the gradient descent method include: Determine the loss function of the minimization objective, and the formula is expressed as:

[0058] Wherein, F is the loss function, max(γ f ) is the maximum frequency response in the sampling signal.

[0059] Establish a parameter set of capacitance and inductance according to the threshold values of capacitance and inductance in the band-pass filter module.

[0060] Calculate the gradients of the required capacitance value and the required inductance value, and the formula is expressed as:

[0061]

[0062] Wherein, σ L is the gradient of the objective function with respect to the inductance, and σ C is the gradient of the objective function with respect to the inductance.

[0063] Iteratively update the inductance and capacitance, and the formula is expressed as:

[0064]

[0065] Wherein, L new is the gradient update value of the inductance value, C new is the gradient update value of the capacitance value, and α is the learning rate of gradient descent.

[0066] Optimize the learning rate in the gradient descent algorithm model through the whale algorithm to find the fluctuations of the frequency response and the optimal capacitance value and optimal inductance value required under the minimum fluctuations.

[0067] The steps for the whale algorithm to optimize the learning rate include: Set the number of whale populations, the maximum number of iterations, and the upper and lower bounds of the search space; Randomly generate a group of candidate whales as the initial population; Initialize the position of the whales in the search space as D; Calculate the fitness of each whale, and the formula is expressed as:

[0068] In the formula, D α is the fitness function, n is the population size, β is an individual whale, and y β is the true value, is the predicted value; Update the position of the whales. The steps to update the position of the whales include the encircling mechanism and the hunting mechanism.

[0069] The formula for updating the position of the whale in the encircling mechanism is expressed as:

[0070] In the formula, H is the distance between the current whale and the prey, D * is the position of the current prey, D(t) is the position of the current whale, D(t + 1) is the position of the whale at iteration t + 1, A and E are coefficient vectors, and t is the current iteration number.

[0071] The formula for updating the spiral position of the whale in the hunting mechanism is expressed as:

[0072] In the formula, H’ is the distance between the current whale and the prey in the hunting mechanism, i∈｛0,1｝ , e is the exponential of the natural logarithm, b is a constant defining the spiral shape.

[0073] The coefficient E is used to control the step size of the whale moving towards the prey or the position of a randomly selected whale, that is, to control the step size of the current solution moving towards the optimal solution or the position of a randomly selected solution. As the number of iterations increases, E linearly decreases from 2 to 0 to achieve the transition from global search to local search. The formula is expressed as:

[0074] In the formula, t max is the maximum number of iteration steps.

[0075] The coefficient A is a random vector used to simulate the random behavior of the whale during the hunting process. Usually, the value of A is randomly generated during the iteration, but it needs to satisfy 1 ≤ A ≤ 2. This can ensure the random movement of the whale in the search space and increase the global search ability of the algorithm. The formula for randomly generating A is expressed as:

[0076] where r is a random number uniformly distributed in the range of [0, 1].

[0077] Recalculate the fitness value for the updated position and update the current optimal solution.

[0078] Repeat updating the position of the whale until the maximum number of iterations is reached, and output the final position of the whale as the optimal solution of the learning rate.

[0079] Input the fluctuations of the frequency response, the initial capacitance value, and the initial inductance value into the gradient descent method to obtain the optimal capacitance value and the optimal inductance value.

[0080] The component regulation module is used to adjust the capacitance value and the inductance value in the band-pass filter module according to the optimal capacitance value and the optimal inductance value. The core function of this module is to monitor and adjust the parameters of the capacitance value and the inductance value in the band-pass filter module in real time to ensure its operation under the best working conditions, thereby improving the efficiency and stability of the overall system. To achieve adaptive regulation, the component regulation module usually adopts advanced control algorithms, and according to real-time data and preset thresholds, automatically adjusts the parameters of the capacitance value and the inductance value in the band-pass filter module to reach the best working state. By adaptively adjusting the optimal values of the components, the component regulation module can effectively improve the performance and reliability of the electronic system and reduce the failure rate.

[0081] The band-pass filter module is integrated with a variable capacitor and a variable inductor to meet the real-time regulation requirements of the component regulation module for the band-pass filter module. The capacitance value change range of the variable capacitor can vary from a few picofarads to several hundred microfarads, depending on the type of the capacitor. The variable inductor usually combines an air-core variable inductor and an iron-core variable inductor. The advantage of the air-core variable inductor is that they can provide a larger inductance value change range, but they may be more sensitive to electromagnetic interference. While the iron-core variable inductor is usually used for a smaller inductance value change range for fine-tuning the inductance.

[0082] Temperature control module: used to detect and adjust the temperature of the band-pass filter module in real time. Ensure that the band-pass filter module operates within the best temperature range, thereby improving performance and reliability. The core function of this module is to monitor and adjust the temperature in the circuit in real time to prevent equipment failures or performance degradation caused by abnormal temperatures.

[0083] The temperature regulation module is usually equipped with highly sensitive temperature sensors, such as thermocouples or RTDs (resistance temperature detectors), to ensure rapid response to temperature changes. The detected temperature data will be transmitted to the control module in the form of analog or digital signals for real-time feedback.

[0084] The temperature regulation module adjusts the temperature of the temperature environment where the band-pass filter module is located in combination with the detected temperature feedback information. Temperature control is a process of precisely controlling the temperature through an adaptive PID control algorithm. The PID control algorithm adjusts the control input to reduce the deviation between the system output and the expected value. Adaptive PID control is an advanced PID control strategy that can automatically adjust the proportional, integral, and derivative parameters to adapt to system dynamic changes and external disturbances. This control method is particularly effective in dealing with nonlinear, time-varying, or uncertain systems. The steps for the temperature regulation unit to use the adaptive PID control algorithm to regulate the temperature of the band-pass filter module are as follows: Establish a mathematical model of the temperature control system, and the steps include: The transfer function formula of the mathematical model is expressed as:

[0085] In the formula, K is the system gain, and τ is the time constant.

[0086] Establish a state space model, and the formula is expressed as:

[0087] In the formula, u(t1) is the output value of the temperature at the time step of t1, x(t1) is the system state, and y(t1) is the output temperature.

[0088] Further design the PID controller, and the formula is expressed as:

[0089]

[0090] In the formula, K p is the proportional gain, K j is the integral gain, K d is the derivative gain, e(t1) is the temperature error, qτ is the derivative representing the time constant τ, is the derivative of the temperature error e(t1) with respect to time t1, T set is the set temperature, T true is the actual temperature.

[0091] To enable the PID controller to have an adaptive ability, adjust the PID parameters according to the real-time feedback of the system, that is, adjust the gain based on the rate of change of the error and the system response. That is, when the error increases, increase K p and K j . When the system response is too fast, reduce K d .

[0092] Optimize the proportional gain, integral gain, and derivative gain of the adaptive PID model through the Grey Wolf Algorithm as follows: Assign a set of PID parameters to each grey wolf, that is, the system gain parameters K p , K j and K d .

[0093] Define the fitness function of the Grey Wolf Algorithm, and the formula is expressed as:

[0094] In the formula, θ is the sum of squares of temperature errors, and the goal is to minimize this value.

[0095] Calculate the sum of squares of temperature errors over the entire time period [0, T] to obtain the fitness value:

[0096] In the formula, Δt1 is the time step.

[0097] Store the fitness value of each grey wolf in an array.

[0098] Furthermore, determine the current optimal solution, that is, the grey wolf with the minimum fitness, and the steps are as follows: Initialize the optimal fitness:

[0099] In the formula, θ best is the optimal fitness.

[0100] Set the initial position of the grey wolf, and the formula is expressed as:

[0101] Traverse the fitness of each grey wolf, which is expressed as: When θ j < θ best , then θ best = θ j , X best = X j In the formula, θ best is the optimal fitness, θ j is the fitness of grey wolf j, X j is the candidate solution corresponding to the fitness of grey wolf j, and X best is the optimal solution corresponding to the grey wolf with the best fitness After the traversal is completed, use the said optimal solution as the optimal proportional gain, optimal integral gain, and optimal derivative gain required in the adaptive PID control algorithm.

[0102] The PID controller optimized by the Grey Wolf Optimizer can effectively find the optimal parameters of the PID controller; control the temperature more precisely, reduce the overshoot and steady-state error, improve the stability and response speed of the control system; better handle the uncertainty and nonlinear characteristics of the system, and improve the control effect.

[0103] Frequency output module: It is used to receive the frequency output by the output signal processing module and display it through the oscilloscope built in the frequency output module. The frequency output module is usually an analog-to-digital converter (ADC), which is used to convert continuous analog signals into discrete digital signals. Usually, the sampling frequency is at least twice the highest frequency of the signal to avoid aliasing.

[0104] In summary, by combining the response frequency, the learning rate in the gradient descent algorithm model is optimized by the Whale Optimization Algorithm to find the optimal capacitance value and optimal inductance value under the minimum passband ripple, solving the problem of non-optimal matching among capacitance, inductance, and response frequency, achieving the best matching among capacitance, inductance, and frequency response, and obtaining the beneficial effect of achieving the best noise reduction.

[0105] By using the adaptive PID control algorithm to realize the temperature regulation of the temperature regulation unit, the influence of temperature on the band-pass filter module is solved, and the temperature of the band-pass filter module is adaptively regulated, and the temperature of the band-pass filter module is accurately regulated, improving the noise reduction efficiency and robustness of the module.

[0106] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative labor.

[0107] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., including several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0108] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A circuit device for reducing the passband ripple of a bandpass filter, characterized in that, Including: A band-pass filter module, an output signal processing module, a component regulation module, and a temperature control module; The band-pass filter module is used to receive frequency signals within a preset frequency range, convert the frequency signals into a sampling frequency, and suppress signals outside the preset frequency range; The output signal processing module is used to construct a capacitance and inductance optimization model based on the gradient descent method, and optimize the capacitance and inductance optimization model using the whale algorithm; input the frequency response, initial capacitance value, and initial inductance value into the capacitance and inductance optimization model to obtain the optimal capacitance value and the optimal inductance value; The component regulation module is used to adjust the capacitance value and inductance value in the band-pass filter module according to the optimal capacitance value and the optimal inductance value; The temperature control module is used to detect and adjust the temperature of the component regulation module in real time.

2. The circuit device for reducing the passband ripple of a band-pass filter according to claim 1, characterized in that, The output signal processing module includes a frequency reception unit, a frequency response unit, and a matching unit; The frequency reception unit is used to receive the sampling frequency; The frequency response unit is used to calculate the frequency response of the sampling frequency and establish a fluctuation set according to the frequency response; The matching unit is used to calculate the fluctuation of the frequency response and calculate the optimal capacitance value and the optimal inductance value required for the fluctuation to reach the minimum value.

3. The circuit device for reducing the passband ripple of a band-pass filter according to claim 2, characterized in that, The formula for the frequency reception unit to calculate the frequency response is expressed as: wherein, γ f is the frequency response value, L is the inductance, C is the capacitance, and f is the frequency.

4. The circuit device for reducing the passband ripple of a band-pass filter according to claim 2, characterized in that, The steps for constructing the capacitance and inductance optimization model include: Establish a basic capacitance and inductance optimization model based on the gradient descent method; Use the whale algorithm to optimize the learning rate of the gradient descent method; Train the basic capacitance and inductance optimization model using the fluctuation set; Retain the model parameters that meet the preset accuracy to obtain the capacitance and inductance optimization model.

5. The circuit device for reducing the passband ripple of a band-pass filter according to claim 4, characterized in that, The gradient descent method includes: Determine the loss function of the minimum passband fluctuation, and the formula is expressed as: where F is the minimum passband ripple loss function, max(γ f ) is the maximum frequency response in the sampling frequency, and min(γ f ) is the minimum frequency response in the sampling frequency; Calculate the gradients of the required capacitance value and the required inductance value, and perform iterative updates in combination with the gradients. The formula is expressed as: where L new is the gradient update value of the required inductance value, C new is the gradient update value of the required capacitance value, and are the gradients of the required inductance value and the required capacitance value respectively, and α is the learning rate of gradient descent.

6. The circuit device for reducing the passband ripple of a bandpass filter according to claim 4, characterized in that, The steps for using the whale algorithm to optimize the learning rate of the gradient descent method include: Set the number of whale populations, the maximum number of iterations, and the upper and lower bounds of the search space; Randomly generate a group of candidate whales as the initial population, and each whale corresponds to a group of the learning rates; Initialize the whale position as D within the search space; Calculate the fitness of each whale, and the formula is expressed as: where D α is the fitness function, n is the population size, β is a whale individual, and y β is the true value, and is the predicted value; According to the fitness, update the position of each whale using the encircling prey and hunting behaviors; Recalculate the fitness value for the updated whale position, and update the current optimal solution according to the maximum value of the fitness; Repeat updating the position of the whale until the maximum number of iterations is reached, and output the whale position with the highest fitness value as the optimal solution of the learning rate.

7. The circuit device for reducing the passband ripple of a bandpass filter according to claim 6, characterized in that, The formula for updating the whale position using the encircling prey is expressed as: Wherein, H is the distance between the current whale and the prey in the surrounded prey, D * is the position of the current prey, D(t) is the position of the current whale, D(t + 1) is the position of the whale at the iteration number t + 1, A and E are coefficient vectors, and t is the current iteration number; The formula for updating the whale position using the hunting behavior is expressed as: Where H' is the distance between the current whale and the prey during the hunting behavior. i ∈{0,1}, e is the base of the natural logarithm, and b is a constant defining the spiral shape.

8. The circuit device for reducing the passband ripple of a bandpass filter according to claim 1, characterized in that, The temperature control module uses an adaptive PID control algorithm to achieve temperature regulation of the temperature environment of the band-pass filter module, and the formula is expressed as: Where, u(t1) is the output value of temperature at the time step of t1, K p is the proportional gain, K j is the integral gain, K d is the derivative gain, τ is the time constant, t1 is the time step, e(t1) is the temperature error, qτ is the differential representing the time constant τ, is the derivative of the temperature error e(t1) with respect to the time t1.

9. The circuit device for reducing the passband ripple of a bandpass filter according to claim 8, characterized in that, The temperature control module uses the grey wolf algorithm to optimize the proportional gain, the integral gain, and the derivative gain of the PID control algorithm, and the formula is expressed as: The traversal of the fitness of each gray wolf is expressed as: when θ j <θ best then θ best =θ j , X best =X j ; where θ best is the optimal fitness, θ j is the fitness of grey wolf j, X j is the candidate solution corresponding to the fitness of grey wolf j, X best is the optimal solution corresponding to the grey wolf with the best fitness; After the traversal is completed, the optimal solution is used as the optimal proportional gain, optimal integral gain, and optimal differential gain required in the adaptive PID control algorithm.

10. The circuit device for reducing the passband ripple of a bandpass filter according to claim 1, characterized in that, It further includes a frequency output module, which is used to receive the sampling frequency and display it through an oscilloscope built in the frequency output module.

Images