MatlabandVB

matlab 源码 KPCA/核PCA 可用于人脸识别(matlab source KPCA/nuclear PCA for Face Recognition)

Generate Rayleigh fading

经典leach算法,是学习leach最好的算法，有详尽的代码注释。(classical algorithm of leach)

说明：  改进的PRI变换应用于重频正弦调制脉冲序列(Improve the PRI transform to sinusoidal modulation pulse sequence re-frequency)

基于无差拍的有源电力滤波器（APF）的仿真设计，包括（谐波检测， 电流跟踪环节） Z域(spwm调制)(Deadbeat based Active Power Filter (APF) simulation design, including (harmonic detection, current tracking links) Z domain (spwm modulation))

这是一个包含simulink模型的主动控制的程序，应用遗传算法求解(This is a program that contains the active control of the simulink model and is solved using genetic algorithms)

在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5—2S时，机动频率越小跟踪精度越高[1]，但机动频率仍然是固定值。本文提出的基于神经网络的机动频率自适应调整方法可以使机动频率随机动而变化，从而提高状态估计的准确性，提高跟踪精度。本文将小波神经网络用于机动目标跟踪中机动频率的自适应调整，该算法对机动目标“当前”统计模型中的机动频率进行实时修改, 从而自适应的改变机动频率,使跟踪算法与目标的真实状态更接近。该算法采用小波神经网络的离线训练，实时性好。(The maneuver of the maneuvering target is uncertain. The maneuvering frequency is constantly changeable, but traditionally it is beforehand determined as a constant based on the target state estimation in the state model of the maneuvering target. The maneuver of the maneuvering target makes the kinematics equation of the target model mismatch with the practical motion model and the tracking error will be increased. Based on the advantages of the self-learning, the rapid convergence rate and the nonlinear approximation ability of the wavelet neural network, it was put forward to be used in the field of target tracking in the paper. The new residual is used as the input of the wavelet neural network, the output of the network is used to adjust adaptively the maneuvering frequency of the CS model. The algorithm is more close to the real state of the target. The simulation results showed that tracking error can be reduced and the tracking accuracy can be improved.)

A/D和D/A转换器模型 对串行和并行输出的8位A/D和D/A转换器进行仿真，转换值范围为0到255，转换采样率为1次/秒。 (A/D and D/A converter model, serial and parallel output of the 8-bit A/D and D/A converter to simulate the conversion values range from 0 to 255, change the sampling rate of 1 times/sec.)

《神经模糊预测控制及其matlab实现》（第3版）matlab程序(Neuro fuzzy predictive control and its matlab implementation (Third Edition) matlab program)

π/4QPSK系统在AWGN信道下的误码率性能(π/4QPSK system in the AWGN channel BER performance)