OFDM

基本PSO算法源代码,可以直接在matlab中运行。效果不错，适合初学者。(Basic PSO algorithm source code can be directly run in matlab. Good results, suitable for beginners.)

spi总线控制器的程序，实现了同步串行接口的输出(On the spi serial bus interface programming, synchronous transfer)

说明：  用MATLAB编写的crc校验查表法解码程序(Prepared using MATLAB CRC checksum decoding procedure look-up table method)

matlab自编函数库，含有大量常用函数。。。。。。。。。。。。。。。。(self matlab function library containing a large number of commonly used functions. . . . . . . . . . . . . . . .)

首先对图像进行了边缘检测，设计相应的结构元素对图像进行腐蚀，再进行图像聚类和填充图像。(First, the image edge detection, the design of structural elements corresponding to the image etched image clustering and then fill the image.)

matlab经典教材并且其中有部分确实写得不错(Matlab classic textbook and some really well-written)

Matlab code for doing DCT and inverse DCT

matlab中一种遗传算法的源程序 很全面 很有用(a genetic algorithm matlab source code is very comprehensive and useful)

水声信道中的稳健均衡算法，包括算法的理论分析，仿真及实验结果(robust equalization algorithm for UWA channels, with experimental results)

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.)