An event-triggered neuron circuit based on volatile memristor

Abstract

This invention relates to an event-triggered neuron circuit based on a volatile memristor, comprising: a signal transmission module and an encoding module; the signal transmission module converts a received light signal into an output voltage and transmits the output voltage to the encoding module; wherein the output voltage is positively correlated with the intensity of the light signal; the encoding module obtains an oscillating encoded signal based on the change in the output voltage. This technical solution converts the light signal into a voltage, and by controlling the change in the output voltage, obtains an oscillating encoded signal consistent with the characteristics of LIF neurons. The output voltage can change according to the increase or decrease in light intensity, which is also consistent with the characteristics of event-driven structures. This achieves voltage encoding output of light changes using a simple circuit structure, and to some extent promotes the development of event-driven structure research in neuromorphic computing.

Description

Technical Field

[0001] This invention relates to the field of electronic information technology, and more specifically, to an event-triggered neuron circuit based on a volatile memristor. Background Technology

[0002] Neuromorphic computing is a computational method that simulates the electrophysiological processes of collaboration between neurons in the human brain. It can be applied to fields such as artificial intelligence, pattern recognition, and control. Unlike the traditional von Neumann architecture, neuromorphic computing does not require large amounts of data transmission and can process more complex information in a more flexible way. Compared to traditional computers, cells in neural networks process vast amounts of information simultaneously, giving neuromorphic computing a significant advantage in simulating the human brain's information processing capabilities.

[0003] Event cameras, also known as event-based cameras or event-driven cameras, are a novel visual sensing technology. They differ significantly from traditional cameras in their data acquisition and representation methods. Instead of capturing the entire scene at a fixed frame rate, event cameras record events based on pixel-level brightness changes. Each pixel in an event camera works independently; when a change in pixel brightness is detected, that pixel triggers an event. Traditional cameras capture the entire scene at fixed time intervals (e.g., 30 or 60 frames per second). Each frame contains static image information of the entire scene. They record every frame of the entire scene, regardless of whether the scene changes. Each frame contains a large amount of redundant information, especially when most of the scene remains unchanged. Limited by a fixed frame rate and relatively low dynamic range, traditional cameras may blur or lose information about fast-moving objects and are prone to losing detail under strong lighting.

[0004] An event camera uses individual pixels to detect changes in brightness and generate events when these changes occur. This structure allows the event camera to respond to brightness changes with extremely high temporal resolution while generating only data relevant to the change, thus significantly reducing data volume and processing requirements. Traditional event camera pixels consist of mixed-signal circuitry, including photosensitive elements, comparators, threshold regulators, addressing logic, timestamp generators, and event output structures. Event cameras have broad application potential in autonomous driving, robot vision, aerospace, and high-speed video capture, especially in scenarios requiring high temporal resolution, low latency, and high dynamic range visual information processing. Combining event-driven computing with neuromorphic computing has wide applications in dynamic image recognition, speed detection, and motion prediction, and can further reduce overall circuit power consumption. However, in current research, the complex structure of individual pixels in event cameras results in large design and manufacturing layouts, making performance testing of individual pixels inconvenient. Differences in different structures directly or indirectly affect overall performance, limiting further reductions in power consumption and structural simplification, thus hindering the application of event cameras in neuromorphic computing. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides an event-triggered neuron circuit based on a volatile memristor.

[0006] According to a first aspect of the present invention, an event-triggered neuron circuit based on a volatile memristor is provided, the event-triggered neuron circuit based on a volatile memristor includes: a signal transmission module and an encoding module;

[0007] The signal transmission module is used to convert the received light signal into an output voltage and transmit the output voltage to the encoding module; wherein the output voltage is positively correlated with the intensity of the light signal.

[0008] The encoding module is used to obtain an oscillation encoding signal based on the change in the output voltage.

[0009] Optionally, the signal transmission module includes: an external gate power supply, an external drain power supply, a phototransistor, and a voltage-transmitting resistor; the positive terminal of the external gate power supply is connected to the gate of the phototransistor, the positive terminal of the external drain power supply is connected to the drain of the phototransistor, the source of the phototransistor is connected to the first terminal of the voltage-transmitting resistor, the negative terminal of the external gate power supply is grounded, the negative terminal of the external drain power supply is grounded, and the second terminal of the voltage-transmitting resistor is grounded.

[0010] Optionally, the signal transmission module is further configured to obtain the current value flowing through the voltage transmission resistor based on the light intensity currently received by the photoelectric thin-film transistor; and to obtain the output voltage based on the current value.

[0011] Optionally, the gate of the photoelectric thin-film transistor is used to detect light intensity.

[0012] Optionally, the encoding module includes: a differential capacitor and a volatile memristor; the first terminal of the differential capacitor is connected to the output voltage, the second terminal of the differential capacitor is connected to the first terminal of the volatile memristor, and the second terminal of the volatile memristor is grounded.

[0013] Optionally, the encoding module is further configured to obtain the charging and discharging current of the differential capacitor based on the output voltage; to obtain a first voltage of the volatile memristor in a high-resistance state and a second voltage of the volatile memristor in a low-resistance state based on the charging and discharging current; and to obtain the oscillation encoding signal based on the first voltage and the second voltage.

[0014] The technical solution provided by this invention may include the following beneficial effects:

[0015] The above technical solution uses a signal transmission module to convert light signals into voltage. By measuring the change in output voltage, an oscillating encoded signal consistent with the characteristics of LIF neurons is obtained. The output voltage can change according to the increase or decrease of light intensity, which is also consistent with the characteristics of event-driven structures. This realizes the voltage encoding output of light changes using a simple circuit structure, which to some extent promotes the development of event-driven structure research in neuromorphic computing.

[0016] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0017] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the following detailed description to explain the invention, but do not constitute a limitation thereof. In the drawings:

[0018] Figure 1 This is a schematic diagram of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment.

[0019] Figure 2 This is a schematic diagram of the structure of a signal transmission module according to an exemplary embodiment.

[0020] Figure 3 This is a schematic diagram illustrating the structure of an encoding module according to an exemplary embodiment.

[0021] Figure 4 This is a schematic diagram of the structure of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment.

[0022] Figure 5 This is an input / output schematic diagram of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment.

[0023] Figure 6 This is a schematic diagram of the output of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment.

[0024] Figure 7 This is a schematic diagram of the output of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment.

[0025] Figure 8 This is a schematic diagram of the output of another event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment. Detailed Implementation

[0026] Figure 1 This is a schematic diagram of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment, such as... Figure 1 As shown, the event-triggered neuron circuit 10 based on volatile memristors includes: a signal transmission module 101 and an encoding module 102;

[0027] The signal transmission module 101 is used to convert the received light signal into an output voltage Vout1 and transmit the output voltage Vout1 to the encoding module 102; wherein, the output voltage Vout1 is positively correlated with the intensity of the light signal.

[0028] Encoding module 102 is used to obtain oscillation encoding signal Vout2 based on the change in output voltage Vout1.

[0029] Optionally, Figure 2 This is a schematic diagram illustrating the structure of a signal transmission module according to an exemplary embodiment, such as... Figure 2 As shown, the signal transmission module 101 includes: an external gate power supply Vg, an external drain power supply Vdd, a phototransistor TFT, and a voltage transmission resistor R; the positive terminal of the external gate power supply Vg is connected to the gate of the phototransistor TFT, the positive terminal of the external drain power supply Vdd is connected to the drain of the phototransistor TFT, the source terminal of the phototransistor TFT is connected to the first end of the voltage transmission resistor R, the negative terminal of the external gate power supply Vg is grounded, the negative terminal of the external drain power supply Vdd is grounded, and the second end of the voltage transmission resistor R is grounded.

[0030] It is understood that the external gate power supply Vg and the external drain power supply Vdd are adjustable voltage sources. This invention uses the external gate power supply Vg to simulate changes in light intensity. The external gate power supply Vg and the external drain power supply Vdd typically keep the photoelectric thin film transistor (TFT) in a saturated operating state. The resistance value of the voltage transmission resistor R is adjustable. When the resistance value of the voltage transmission resistor R is larger, the output voltage Vout1 is larger. When the resistance value of the voltage transmission resistor R is smaller, the output voltage Vout1 is smaller.

[0031] Optionally, the signal transmission module is also used to obtain the current value flowing through the voltage transmission resistor R based on the light intensity currently received by the photoelectric thin film transistor TFT; and to obtain the output voltage Vout1 based on the current value.

[0032] Optionally, the gate of the photoelectric thin-film transistor (TFT) is used to detect light intensity.

[0033] Understandably, this invention uses a photoelectric thin-film transistor (TFT) to sense light intensity, forming a signal transmission module that converts the light intensity into an output voltage Vout1 proportional to it, and transmits it to the encoding module. The photoelectric thin-film transistor is an active electronic device. Unlike ordinary transistors, it is small in size and can sense light intensity. Under illumination or de-illumination conditions, photogenerated carriers are generated or recombine in the conductive channel, thereby increasing or decreasing the channel current. A resistor is connected in series at its source stage; the increased current causes the potential difference across the resistor to increase or decrease, resulting in an increase or decrease in the output voltage. Thus, it has the function of converting light intensity into voltage and transmitting it.

[0034] Optionally, Figure 3 This is a schematic diagram illustrating the structure of an encoding module according to an exemplary embodiment, such as... Figure 3 As shown, the encoding module 102 includes: a differential capacitor C and a volatile memristor TS; the first terminal of the differential capacitor C is connected to the output voltage Vout1, the second terminal of the differential capacitor C is connected to the first terminal of the volatile memristor TS, and the second terminal of the volatile memristor TS is grounded.

[0035] Optionally, the encoding module is further configured to obtain the charging and discharging current of the differential capacitor C based on the output voltage Vout1; to obtain the first voltage of the volatile memristor TS in the high-resistance state and the second voltage of the volatile memristor TS in the low-resistance state based on the charging and discharging current; and to obtain the oscillation encoding signal Vout2 based on the first voltage and the second voltage.

[0036] It is understandable that the differential capacitor C acts as a differentiator. A capacitor is a passive electronic component, and the amount of charge stored inside is proportional to the potential difference between its positive and negative terminals. When the potential difference increases, the differential capacitor C is in a charging state; when the potential difference decreases, it is in a discharging state. During charging and discharging, the differential capacitor C can be considered as a short circuit, and after charging is complete, it can be considered as an open circuit. Therefore, the differential capacitor C has the function of detecting signal changes. A volatile memristor TS is used to simulate the electrical impulse behavior of LIF neurons. The volatile memristor TS is a passive electronic component. It is similar to a resistor, capable of generating and maintaining current through a device. However, unlike a resistor, the volatile memristor TS can still "remember" the amount of charge that passed through it after the power supply is disconnected. The volatile memristor TS has two important parameters: the threshold voltage Vth and the holding voltage Vhold. The threshold voltage is the voltage value required for the memristor to transition from one resistive state to another. When the applied voltage exceeds this threshold, the volatile memristor TS undergoes a change in resistance. For example, when the applied voltage exceeds the threshold voltage Vth, the volatile memristor TS switches from a high-resistance state to a low-resistance state, and its resistance value becomes lower. The holding voltage Vhold refers to the minimum voltage required for the volatile memristor TS to maintain its low-resistance state after switching to it. Once the volatile memristor TS switches to a new resistance state via a signal exceeding the threshold voltage Vth, it can maintain its resistance state above the threshold voltage as long as no voltage sufficient to trigger a state change is applied. Due to special manufacturing processes, volatile memristors possess parasitic capacitance internally, analogous to nerve cells, called membrane capacitance. Under certain voltage conditions, these capacitances can produce oscillating behavior similar to neuronal signal output.

[0037] It is worth mentioning that, due to the involvement of the differential capacitor C, this process only occurs when the light intensity changes. If the light intensity remains unchanged, or if the voltage change caused by the change in light intensity is insufficient to cause the volatile memristor to switch its resistance state through detection by the differential capacitor C, then the oscillation code signal Vout2 will not be generated.

[0038] Understandably, the capacitance value of the differential capacitor C is set according to the actual situation. The first terminal of the differential capacitor C is used to receive the output voltage Vout1 of the signal transmission module 101. The current flowing through the volatile memristor TS is obtained according to the change of the output voltage Vout1. The larger the capacitance value of the differential capacitor C, the slower the output voltage Vout1 charges the differential capacitor C, and the longer the current flowing through the volatile memristor TS lasts. The smaller the capacitance value of the differential capacitor C, the faster the output voltage Vout1 charges the differential capacitor C, and the shorter the current flowing through the volatile memristor TS lasts. The volatile memristor TS can be regarded as a resistor that switches back and forth between different resistance states. The voltage across the volatile memristor TS can be obtained by multiplying the current flowing through the volatile memristor TS by the resistance value of the volatile memristor TS in different states. By comparing the voltage across the volatile memristor TS with the threshold voltage Vth and the holding voltage Vhold of the volatile memristor TS, the resistance state of the volatile memristor TS at the next moment can be obtained. The output Vout2 of the encoding module can be obtained by the spontaneous switching of the voltage across the volatile memristor TS.

[0039] In one implementation, in the initial state of the event-triggered neuron circuit based on the volatile memristor TS, the volatile memristor TS is in a high-resistance state, with a resistance equal to its high-resistance resistance. The external gate voltage source Vg and the external drain voltage source Vdd are given certain values. The phototransistor TFT is in the saturation or linear region. At this time, there is a certain voltage across the voltage-transmitting resistor R, but the voltage remains constant. There is a certain voltage across the differential capacitor C, but no current flows through the differential capacitor C. Therefore, the voltage across the volatile memristor TFT is 0. Because the phototransistor... When the light intensity received by the gate of a thin-film transistor (TFT) changes, if the light intensity increases, photogenerated carriers will be generated inside the TFT. This increases the current flowing through the TFT while the external gate voltage source Vg and external drain voltage source Vdd remain constant. Since the resistance of the voltage transmission resistor R remains unchanged, the voltage across R increases with the increase in light intensity. Consequently, the potential at the end of the differential capacitor C connected to the signal transmission module 101 rises, and the differential capacitor C enters a charging process until it is connected to the signal transmission module 101. One end of module 101 has the same potential as the end of the voltage-transfer resistor R connected to the source stage of the phototransistor TFT. During charging, current flows through the differential capacitor C and then through the volatile memristor TS. At this time, the voltage across the volatile memristor TS is determined by the high-resistance state and the current flowing through the differential capacitor C. If the voltage across the volatile memristor TS exceeds the threshold voltage during charging, the volatile memristor TS will immediately change to a low-resistance state. At this time, the voltage across the volatile memristor TS is determined by the low-resistance state and the current flowing through the differential capacitor C. When the voltage across the volatile memristor TS is less than the holding voltage, TS immediately changes to a high-resistance state. Therefore, during the charging process of the differential capacitor C, TS continuously changes its resistance, resulting in an oscillating output similar to neuron coding at the end of TS connected to the differential capacitor C. It is worth mentioning that during the charging process of the differential capacitor C, the direction of the current is taken as the positive direction, so the oscillation coding signal Vout2 is a positive output. It can be understood that when the charging process of the differential capacitor C ends and the current becomes 0, there is no oscillation output.If the light intensity decreases, photogenerated carriers will recombine inside the phototransistor TFT. This reduces the current flowing through the TFT while the external gate voltage source Vg and external drain voltage source Vdd remain constant. Since the resistance of the voltage-transfer resistor R remains unchanged, the voltage across R decreases as the light intensity decreases. Consequently, the potential at the end of the differential capacitor C connected to the signal transmission module 101 decreases, and the differential capacitor C enters a discharge process until its potential equals the potential at the end of the voltage-transfer resistor R connected to the source stage of the phototransistor TFT. During this discharge, current flows through the differential capacitor C and the volatile memristor T. At this point, the voltage across the volatile memristor TS is determined by the high-resistance state and the current flowing through the differential capacitor C. If the voltage across the volatile memristor TS is greater than the threshold voltage during discharge, it will immediately change to a low-resistance state. If the voltage across the volatile memristor TS is less than the holding voltage during discharge, it will immediately change to a high-resistance state. Therefore, during the discharge of the differential capacitor C, the volatile memristor TS continuously changes its resistance, resulting in an oscillating output at the end connected to the differential capacitor C, similar to neuron coding. During the discharge of the differential capacitor C, the direction of the current is negative, so the oscillation coding signal Vout2 is an inverted output. It can be understood that when the charging process of the differential capacitor C ends, the current becomes 0, and there is no oscillation output.

[0040] The voltage transmission resistor R plays two roles in the charging and discharging process of the differential capacitor C: during the charging process, the value of the voltage transmission resistor R directly determines the potential level of the differential capacitor C connected to the signal transmission module 101; during the discharging process, the value of the voltage transmission resistor R directly determines the discharging speed of the differential capacitor C. Therefore, in the implementation process, selecting a suitable resistance value of the voltage transmission resistor R becomes particularly important.

[0041] In one implementation, Figure 4 This is a schematic diagram illustrating the structure of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment. Figure 4 As shown, according to Figure 2 and Figure 3 The structure of the signal transmission module and the structure of the encoding module can be connected to an event-triggered neuron circuit based on volatile memristors.

[0042] In one embodiment, to better demonstrate the effects of the present invention, a simulation experiment can be conducted based on the present invention. The volatile memristor TS has a low-resistance state of 2kΩ and a high-resistance state of 80kΩ. The voltage transmission resistor R is 22kΩ, the differential capacitor C is 33nΩ, the external drain power supply Vdd is 10V, the gate pulse of the phototransistor TFT is 10V with a pulse period of 200ms, a high level of 10ms, a rise time of 1ms, and a fall time of 1ms, and the external gate power supply Vg has a high level of 10V and a low level of 0V, with a pulse period of 200ms, a high level of 10ms, a rise time of 1ms, and a fall time of 1ms. Figure 5 This is a schematic diagram of the input and output of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment. Figure 6 This is a schematic diagram of the output of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment. Figure 5 and Figure 6 As shown, green represents the output of the oscillation encoding signal Vout2, and blue represents the change in the external gate power supply Vg. Figure 7 This is a schematic diagram of the output of an event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment. Figure 8 This is a schematic diagram of the output of another event-triggered neuron circuit based on a volatile memristor, according to an exemplary embodiment. Figure 7 This is the positive output corresponding to the rising edge of the gate pulse of the photoelectric thin-film transistor (TFT). Figure 8 This is the negative output corresponding to the falling edge of the gate pulse of the photoelectric thin-film transistor (TFT).

[0043] The above technical solution uses a photoelectric thin-film transistor (TFT) to detect light intensity and obtain an output voltage Vout1 proportional to the light intensity. Changes in light intensity affect changes in the output voltage Vout1. The change in output voltage Vout1 is then detected by a differential capacitor C to obtain the current flowing through the volatile memristor TS. When the volatile memristor TS is in a high-resistance state, the current flowing through it keeps the volatile memristor TS at a high voltage across its terminals. When this voltage exceeds the threshold voltage of the volatile memristor TS, it switches to a low-resistance state. At this point, the current flowing through the volatile memristor... The current in resistor TS increases accordingly, but the voltage across volatile memristor TS is insufficient to maintain its low-resistance state. This causes volatile memristor TS to switch back and forth between high and low resistance states, resulting in the oscillating encoded signal Vout2. The output oscillating encoded signal Vout2 is consistent with the characteristics of the LIF neuron circuit and is only output when a change in light intensity is detected, exhibiting event-triggered characteristics. This realizes an event-driven structure for brain-like computing using a simple circuit system, which to some extent promotes the development of research on brain-like computing structures with event-driven characteristics.

[0044] The preferred embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the specific details of the above embodiments. Within the scope of the technical concept of the present invention, various simple modifications can be made to the technical solution of the present invention, and these simple modifications all fall within the protection scope of the present invention.

[0045] It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the present invention will not describe the various possible combinations separately.

[0046] Furthermore, various different embodiments of the present invention can be combined in any way, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed by the present invention.

Claims

1. An event-triggered neuron circuit based on a volatile memristor, characterized in that, The event-triggered neuron circuit based on a volatile memristor includes a signal transmission module and an encoding module. The signal transmission module includes an external gate power supply, an external drain power supply, a phototransistor, and a voltage-transmitting resistor. The positive terminal of the external gate power supply is connected to the gate of the phototransistor, the positive terminal of the external drain power supply is connected to the drain of the phototransistor, the source of the phototransistor is connected to the first terminal of the voltage-transmitting resistor, the negative terminal of the external gate power supply is grounded, the negative terminal of the external drain power supply is grounded, and the second terminal of the voltage-transmitting resistor is grounded. The encoding module includes a differential capacitor and a volatile memristor. The first terminal of the differential capacitor is connected to the output voltage, the second terminal of the differential capacitor is connected to the first terminal of the volatile memristor, and the second terminal of the volatile memristor is grounded. The signal transmission module is used to convert the received light signal into an output voltage and transmit the output voltage to the encoding module; wherein the output voltage is positively correlated with the intensity of the light signal. The signal transmission module is also used to obtain the current value flowing through the voltage transmission resistor based on the light intensity currently received by the photoelectric thin-film transistor; and to obtain the output voltage based on the current value; The encoding module is used to obtain an oscillation encoding signal based on the change in the output voltage; The encoding module is further configured to obtain the charging and discharging current of the differential capacitor based on the output voltage; to obtain a first voltage of the volatile memristor in a high-resistance state and a second voltage of the volatile memristor in a low-resistance state based on the charging and discharging current; and to obtain the oscillation encoding signal based on the first voltage and the second voltage.

2. The event-triggered neuron circuit based on volatile memristors according to claim 1, characterized in that, The gate of the photoelectric thin-film transistor is used to detect light intensity.

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