167 results about "Power matrix" patented technology

A system and method for making semiconductor die connections with through-silicon vias (TSVs) are disclosed. TSVs are formed through the substrate to allow for signal connections as well as power and ground connections. In one embodiment this allows these connections to be made throughout the substrate instead of on the periphery of the substrate. In another embodiment, the TSVs are used as part of a power matrix to supply power and ground connections to the active devices and metallization layers through the substrate.

A modular adaptive power management center integrating control and management of multiple electrical power sources such as locally generated solar or wind power, connections to an electrical utility service provider, battery power, and others. The system increases system efficiency by monitoring load requirements and matching available power sources in real time. A wall mounted rack system houses a system backplane and a main system microprocessor. The backplane accepts plug-in power modules including power converters each dedicated to managing one of various energy sources such as local wind or solar sources, as well as utility grid connections and battery backup systems. The system also includes a backup battery bank and a battery power module to control charge/discharge activity of the batteries. A variety of user interfaces are provided including via a local LCD display, LED indicators, and remote access and monitoring through an Internet connection and browser window. The modular nature of the design allows a homeowner/user to “plug-in” additional modules as new power sources become available.

The temperature distribution associated with a design of an integrated circuit is calculated by convoluting a surface power usage represented by a power matrix with a heat spreading function. The heat spreading function may be calculated from a simulation of a point source on the integrated circuit using a finite element analysis model of the integrated circuit or other techniques. To account for spatial variations on the chip, the heat spreading function may be made dependent on position using a position scaling function. Steady-state or transient temperature distributions may be computed by using a steady-state or transient heat spreading function. A single heat spreading function may be convolved with various alternative power maps to efficiently calculate temperature distributions for different designs. In an inverse problem, one can calculate the power map from an empirically measured temperature distribution and a heat spreading function using various de-convolution techniques. While the forward problem is analogous to image blurring, the inverse problem is analogous to image restoration.

A multichannel source activity detection system, e.g., a voice activity detection (VAD) system, and method that exploits spatial localization of a target audio source is provided. The method includes the steps of receiving a mixed sound signal by at least two microphones; Fast Fourier transforming each received mixed sound signal into the frequency domain; filtering the transformed signals to output a signal corresponding to a spatial signature of a source; summing an absolute value squared of the filtered signal over a predetermined range of frequencies; and comparing the sum to a threshold to determine if a voice is present. Additionally, the filtering step includes multiplying the transformed signals by an inverse of a noise spectral power matrix, a vector of channel transfer function ratios, and a source signal spectral power.

The invention discloses a Freeman decomposition and homo-polarization rate-based polarized synthetic aperture radar (SAR) image classification method for mainly solving the problems of higher calculation complexity and poor classification effect in the prior art. The method comprises the following steps of: (1) inputting a covariance matrix of polarized SAR data; (2) performing Freeman decomposition on the input matrix to acquire three types of scattering power matrixes of plane scattering, dihedral angle scattering and volume scattering; (3) performing initial division on the polarized SAR data according to the three types of scattering power matrixes; (4) calculating the homo-polarization rate of all pixel points of the polarized SAR data of each class; (5) selecting a threshold value, and dividing the polarized SAR data of each class in the step (3) into 3 classes according to the homo-polarization rate, so that the whole polarized SAR data are divided into 9 classes; and (6) performing repeated Wishart iteration and coloring on the division result of the whole polarized SAR data to obtain a final color classification result graph. Compared with the classical classification method, the method has the advantages that the division of the polarized SAR data is stricter, the classification result is obvious and the calculation complexity is relatively low.

The invention discloses a clutter suppression method based on knowledge-assisted sparse iterative covariance estimation, and solves the problem of poor clutter suppression performance of the conventional space-time adaptive processing technology because of non-uniformity of the clutter environment. The implementation steps are listed as follows: computing an airborne radar space-time steering vector matrix; determining an initial clutter power matrix and constructing an intermediate variable; computing a clutter power matrix in iteration by means of the intermediate variable; performing iteration to obtain the final clutter power matrix; determining a space-time covariance matrix constructed by the data of one unit to be detected and the corresponding weight; and traversing all the units to be detected so as to obtain the space-time adaptive processing result. The clutter covariance matrix is reconstructed by using the data of the units to be detected so as to avoid non-uniformity of the training samples, effectively suppress high ground clutters and improve the detection performance of the slow moving target; and the computational burden is low, the real-time performance is betterand engineering implementation is easy so that the clutter suppression method is suitable for the airborne radar to suppress the high ground clutters in the non-uniform environment and detect the slow ground moving target.

The method comprises: the terminal gets the initial data, and uses the predetermined data-interval sliding to get the average power value and amplitude of each length-predetermined data sequence. Wherein, the terminal makes the sliding multiple correlation calculation for the initial data and the downlink synchronous code to get a correlation matrix, and after mean amplitude normalization, gets its correlation power matrix; searching the maximum power value more than the system threshold from the correlation matrix, and determines the downlink synchronous code and its location in the received data. The apparatus thereof comprises: a data receiving unit, a power calculation unit, an amplitude calculation unit, a sliding multiple correlation calculation unit, a normalization unit and a power comparison unit.

The invention discloses an aircraft radar clutter inhibiting method based on a knowledge assisting sparse gradient minimum variance. According to the main thought, the method comprises the steps of determining an aircraft radar and obtaining Nmax pieces of range gate radar echo data and Nmax pieces of to-be-detected unit data respectively; then determining a clutter ridge; making l belong to {1,2,...,Nmax} and calculating a final clutter power matrix of the l to-be-detected unit data xl on the clutter ridge; utilizing the final clutter power matrix of the l to-be-detected unit data xl on the clutter ridge to calculate a rebuilt space-time two-dimensional covariance matrix of the l to-be-detected unit data xl; making the value of l added with 1 until a rebuilt space-time two-dimensional covariance matrix of the Nmax to-be-detected unit data xl is obtained; utilizing the rebuilt space-time two-dimensional covariance matrix of the Nmax to-be-detected unit data tocalculate the weight used for processing the Nmax to-be-detected unit data and then obtain a space-time self-adaptive processing result, wherein the space-time self-adaptive processing result isthe aircraft radar clutter inhibiting result based on the knowledge assisting sparse gradient minimum variance.

The invention relates to the field of a wireless communication technique, in particular to a method and a device for resource allocation on allowance adaptive criterion; the method comprises the steps: proportionally allocating sub-carrier numbers to users according to user priority; determining a modulation manner according to information channel conditions; calculating a sub-carrier allocation matrix according to a power matrix, discretely processing the sub-carrier allocation matrix, calculating an energy function according to the sub-carrier allocation matrix subjected to the discrete processing; if it satisfies a quit condition, exiting iteration; or else, updating the power matrix and then repeating the above procedures. Based on the allowance adaptive criterion and according to the sub-carrier numbers allocated to users and the bit number determined by the modulation manner, the total transmitting power of the system is minimized and the optimal sub-carrier allocation matrix is output.

The invention discloses an insect characteristic parameter inversion method based on the characteristic values of a polarization power matrix. The research on the polarization invariants of a polarization scattering matrix shows that the two characteristic values lambda 1 and lambda 2 (lambda 1 >= lambda 2) of a Graves power matrix have a strong correlation with the body length and body weight oflarge insects and small insects. On the basis, a method for inverting the body length and body weight of insects using lambda 1 of large insects and lambda 2 of small insects is presented, and a method for distinguishing between large insects and small insects is given. The measurement of body length parameters of insects is realized for the first time. The error of body weight inverted using themethod of the invention is lower than the error of body weight inverted using the traditional method. The ability of VLR (Vertical Looking Radar) to measure the biological parameters of insects is significantly enhanced. The ability to identify the species of migratory insects will be greatly improved. The method is of great significance to the research on the air ecological system and the management of insect pests.

The invention relates to a digital light processing (DLP) display system and discloses a DLP display system and display control method of a laser light source, which are used for improving the utilization efficiency of the light source. The display system comprises a machine core mainboard, a digital signal processor (DSP) control module, an initialization module, a brightness-power matrix module, a fluorescent pink wheel and light filtering color wheel system, a DLP driving module, a blue laser light source and driving module, an optical imaging system and a screen, wherein the DSP control module is connected with the machine core mainboard, the brightness-power matrix module, the initialization module, the blue laser light source and driving module and the DLP driving module, the initialization module is connected with the brightness-power matrix module and the blue laser light source and driving module, the blue laser light source and driving module is connected with the fluorescent pink wheel and light filtering color wheel system, and the optical imaging system is connected with the DLP driving module, the fluorescent pink wheel and light filtering color wheel system and the screen. The DLP display system is suitably used for a DLP display screen.

A method of constructing wind power connection system model based on measured data includes following steps. Operating data is selected in a preset time of each wind turbine in a wind farm. A wind speed matrix and a active power matrix of sampling points are constructed based the operating data. A wind speed model of the wind farm is obtained based on the wind speed matrix and the active power matrix.

The invention discloses a wind electricity connection system model based on measured data. The establishment of the model mainly comprises the following steps that operating data, within a preset period, of each wind turbine of a wind electricity plant to be measured are selected; based on the obtained operating data, within the preset period, of each wind turbine of the wind electricity plant, a sampling point wind speed matrix and a sampling point active power matrix are established; based on the obtained sampling point wind speed matrix and the obtained sampling point active power matrix, calculation is conducted, and a wind speed model of the wind electricity plant to be measured is obtained. The wind electricity connection system model based on the measured data can overcome the defects that in the prior art, the problems of dispersion of the wind electricity plant cannot be solved, and the output power error is large and has the advantages of being capable of solving the problem of dispersion of the wind electricity plant and small in output power error.

The invention discloses a wind power plant marker post draught fan selection method based on principal component analysis. The method includes the steps of acquiring a historical output power curve of each draught fan in a wind power plant, establishing a draught fan output power matrix according to historical output power of each draught fan in the wind power plant, carrying out the principal component analysis on the draught fan output power matrix after preprocessing the draught fan output power matrix, and with principal components with class distinction degrees as a basis for marker post draught fan selection, selecting the marker post draught fans. The wind power plant marker post draught fan selection method based on the principal component analysis can overcome the shortcomings of low selection efficiency, poor selection effects and the like in the prior art, and is high in selection efficiency and good in selection effect.

The invention provides an adaptive filtering method of power signals in load decomposition. The impulse noise in power signals can be effectively filtered. The method comprises the following steps: collecting a power signal sequence, converting the power signal sequence into a power matrix; constructing a transformation operator matrix according to the converted power matrix; constructing a measurement matrix; determining a filtering weight, and iteratively updating a power matrix according to the obtained transformation operator matrix, the filtering weight and the constructed measurement matrix, until the current number of iterations is equal to the length of the power signal sequence; and converting the currently obtained power matrix to generate a power signal sequence with filtered noise. The invention relates to the power field.

The invention provides a power signal filtering method for switching event detection, which is used for solving the problem that in the prior art the work signal filtering which have background noisewith obvious non-stationarity and non-Gaussian characteristics cannot effectively and difficult to carry out the switch event detection accurately. The method comprises the following steps of: carrying out the summation of all scales on the filtered power signal to obtain the filtered power matrix. The power signal filtering method for switching event detection power carrying out the multi-scale summation after the power signal is filtered, filtering the voice of the non-stationarity and the non-Gaussian effectively, filtering the power signal effectively and carrying out the precise switch event detection, the filtering method is simple, the calculation speed is high, and therefore complete the accurate decomposition of the household electrical load.

The invention discloses a cognitive radio network frequency spectrum distribution method based on embedded particle swarm gaming. The method includes extracting the characteristic information of cognitive users; establishing a non-cooperative gaming model based on the characteristics of the cognitive users; resolving the gaming model by means of inner and outer particle swarm algorithms, namely, an embedded particle swarm algorithm; resolving and calculating the channel preference set of each cognitive user in the gaming model by means of the inner particle swarm algorithm based on the characteristics of the cognitive user; resolving the non-cooperative gaming model by means of the outer particle swarm algorithm based on the channel preference set of each cognitive user, and outputting the optimal frequency spectrum distribution result and a corresponding power matrix. Under the underplay frequency spectrum sharing manner, an optimal frequency spectrum distribution scheme is obtained by means of the embedded particle swarm algorithm. The method provided combines the game theory method and the particle swarm algorithm, the channel distribution and power control, rapidly distributes frequency spectrum sources, and moreover, maximizes the benefits of the cognitive users and the system profits within the maximum tolerable interference threshold of a main user.

The invention provides an extraction method of a typical working condition curve of an energy storage system and an evaluation system thereof. The method comprises the following steps: reading operation data of a new energy power generation system and the energy storage system; determining or reading the charge and discharge power data of the energy storage system within a collection time, and forming a charge and discharge power matrix; obtaining a characteristic charge and discharge power value vector at a k moment according to interval distribution properties of a power value of the energy storage system; determining a typical power value of the energy storage system at the k moment; eliminating the power of the energy storage system with relatively small amplitude, and determining the typical power value of the energy storage system at the k moment; integrating the typical power value, and determining the typical power value of the energy storage system at the k moment; analyzing and integrating the typical power values at all moments to obtain the typical working condition curve of the energy storage system; and evaluating the typical working condition curve. By adoption of the extraction method provided by the invention, the operation reliability and stability of the new energy and energy storage hybrid power generation system are improved.

A power grid multiple major failure recognition method based on a linear weighting method comprises the steps as follows: establishing an electrical power system graph theory model and a Laplacian matrix corresponding to the electrical power system graph theory model according to a topological connection relation; establishing a node active power matrix according to a node property and size of an active power; establishing multiple major failure objective function by using the linear weighting method; calculating product of a generalized inverse matrix of the Laplacian matrix and the node active power matrix; establishing a failure preliminary screening matrix according to a vector corresponding to an exact solution; calculating fault component number corresponding to each column vector in the failure preliminary screening matrix; determining weight coefficient in the objective function according to concern extent of an operating crew and screening the column vector which enables the objective function to obtain a minimum value. The power grid multiple major failure recognition method based on the linear weighting method of the invention has important guiding significance for formulating effective prevention and control measures and solving a column control strategy to recognize the multiple major failure.

A three-phase unbalanced load adjustment method based on the power and electricity consumption of a low-voltage power distribution network comprises the following steps of 1, acquiring the power dataof the low-voltage power distribution network, establishing an active power matrix, and calculating the average active power, the average active power and the three-phase average total power of the phases A, B and C according to the active power matrix; 2, obtaining a calculation formula for calculating the three-phase unbalance degree in the low-voltage power distribution network by the active power; 3, calculating the total unbalance degree of the low-voltage power distribution network by adopting the active power; 4, when the total unbalance degree is larger than a set threshold value, solving the active power adjustment amount; and 5, according to the active power adjustment amount, solving a user needing phase modulation and carrying out phase modulation on the user. According to themethod, the problem of misadjustment caused by the random load access or fluctuation when the load current is detected on a site to guide the load adjustment is avoided, the working efficiency is improved, and guidance can be provided for the user to optimize the access phase selection, and therefore the three-phase imbalance degree of the low-voltage distribution network is restrained.

The invention discloses a method for classifying polarimetric synthetic aperture radar (SAR) images on the basis of scattered power and intensity combined statistics. The method for classifying the polarimetric SAR images on the basis of the scattered power and the intensity combined statistics mainly solves the problem that in the prior art, zones with similar scattering properties are difficult to distinguish and classification numbers are fixed. The method is achieved by the following steps that: utilizing a Lee filter to conduct filtering on a coherence matrix T, utilizing Freeman decomposition to obtain a power matrix, utilizing eigenvalue decomposition to obtain an intensity matrix, conducting 8 neighborhood averaging on the power matrix and the intensity matrix respectively, selecting a k class homogeneous zone as a training sample, utilizing an EM algorithm to estimate parameters of probability density distribution functions of the power matrix and the intensity matrix of a k class sample, solving joint probability distribution of the power matrix and the intensity matrix of the k class sample, and conducting Bayesian classification on polarimetric SAR data to be classified to obtain classification results. The method for classifying the polarimetric SAR images on the basis of the scattered power and the intensity combined statistics has the advantages of being good in the classification effect of the polarimetric SAR images, and can be further used for target detection and target identification of the polarimetric SAR images.

The invention discloses a SCMA resource dynamic optimal distribution method. For an uplink grouping user accessing to a base station by applying SCMA technology, the sub-carrier distribution and the power distribution of the in-group user are optimized, thereby establishing an optimization model based on the maximized uplink SCMA system and rate. The method comprises the following steps: initializing a random mapping matrix F0 and an equipower distribution matrix P0, and computing to obtain an interference matrix I0; optimally updating the mapping matrix F by using a sub-carrier distribution optimal algorithm according to the obtained interference matrix I0; solving the power distribution of the sub-carrier according to the obtained interference matrix I and the optimized mapping matrix F,namely obtaining a power matrix P; and updating the interference matrix I, and accomplishing multi-turn iterative optimization and corresponding power distribution on the mapping matrix F by using the sub-carrier optimal algorithm until the iteration is reasonably terminated, namely obtaining a sub-carrier distribution scheme and a power distribution scheme. The total system volume is effectivelyimproved.

The invention relates to the technical field of radar target detection, and in particular, relates to an FPGA-based two-dimensional ordered statistical constant false alarm detector implementation method. According to the method disclosed by the invention, detection is carried out in each clock period from two-dimensional power matrix input, so that the repeated reading time delay of the data cache is reduced, and the detection speed can be effectively improved. Aiming at the condition of large calculated amount in a traditional OS-CFAR (Ordered Statistical Constant False Alarm Rate) sorting process, the FPGA implementation method is completed by adopting parallel comparison, so that the sorting complexity is reduced. The reusability of a module is fully considered, two-dimensional slidingwindow structure setting is completed through a shifting register set, two-dimensional OS-CFAR detection is achieved, and BRAM memory resources and DSP resources of the FPGA can be saved.