HopfieldExperiment

CDMA系统中智能天线盲自适应算法的研究，应该会有帮助的(CDMA smart antenna system, blind adaptive algorithm)

Matlab编程实现FFT变换及频谱分析的程序代码，能出结果，不错(Matlab Programming FFT transform and spectral analysis of the program code to the results, it is true)

Haralick texture descriptor

说明：  用于同时送取货且带时间窗的VRP问题的标准solomon算例。(A standard Solomon example for VRP Problem with time window and simultaneous delivery and pickup.)

常用的z变换程序-,matlab,matlab例程 /matlab (common z transformation process-, Matlab and Matlab routines/Matlab)

Several numeric methods in matlab

QPSK modulation system with recover loops(This is a model of a QPSK modulation system for transmission over a bandpass channel with fc = 100 Hz and B = 30 Hz and AWGN at the receiver. SRRC fi lters with excess bandwidth α = 0.18 are employed. The receiver includes an NDA timing recovery loop followed by a DD phase recovery loop. The transmitter?s symbol period is T and set to a value of 100 ms. The symbol period at the receiver is Tr. The model will produce six windows: Two constellation plots and two eye diagrams (for the real part only), at the output of the matched fi lters and after the recovery loops a plot of the phase error (output of the NCO) and a plot of the fractional timing error (used in the interpolator). The frequency off set at the receiver is denoted by deltaf. The model simulates the transmission of 8000 QPSK symbols.)

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)

用matlab实现的FIR滤波器，滤波效果很好。(FIR matlab filter)

基于粒子群优化算法(PSO)确定参数的脉冲欧和神经网络滤波方法。利用粒子群优化算法(PSO)确定pcnn图像滤波参数，对图像进行滤波(Based on Particle Swarm Optimization (PSO) to determine the parameters of the pulse in Europe and neural network filtering method. The use of particle swarm optimization (PSO) to determine PCNN parameters of image filtering, image filtering)