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无约束连续函数优化的人工鱼群算法通用MATLAB源码.rar

本书对matlab的基础及应用进行了详细介绍，适合matlab初学者学习。(The book and applications on the basis of matlab described in detail, suitable for beginners to learn matlab.)

说明：  在MATLAB下实现的KALMAN滤波，一个二维平面(In MATLAB to achieve the Kalman filter, a two-dimensional plane)

这个程序关于语音信号的消噪，实现了一个基于递归最小二乘法的自适应噪声抵消器(This program about the speech signal de-noising, implements a recursive least squares based adaptive noise canceller)

用matlab将图片进行运动模糊处理，再分别用直接你滤波法，维纳滤波法来对图片进行复原(Using matlab motion blur the picture, and then were used to direct your filtering, Wiener filtering method to recover the picture)

An important aspect of an ANN model is whether it needs guidance in learning or not. Based on the way they learn, all artificial neural networks can be divided into two learning categories - supervised and unsupervised. • In supervised learning, a desired output result for each input vector is required when the network is trained. An ANN of the supervised learning type, such as the multi-layer perceptron, uses the target result to guide the formation of the neural parameters. It is thus possible to make the neural network learn the behavior of the process under study. • In unsupervised learning, the training of the network is entirely data-driven and no target results for the input data vectors are provided. An ANN of the unsupervised learning type, such as the self-organizing map, can be used for clustering the input data and find features inherent to the problem.

基于支持向量机（SVM）回归的MATLAB演示程序(Based on support vector machine (SVM) regression of the MATLAB demo)

CLPF 理想低通滤波ICHPF 理想高通滤波 的实现用于图像的处理(CLPF ideal low-pass filter ICHPF ideal realization of high-pass filtering for image processing)

RNA 和 DNA序列模拟 基因建模 数值模拟 采用matlab 编写 能计算几千个 基因点的特性和行为(In one type of gene expression analysis, fluorescently tagged messenger RNA from different cells are hybridized to a microscopic array of thousands of complimentary DNA spots that correspond to different genes. Illuminated spots emit different color light, indicating which genes are expressed (e.g., green=control, red=sample, yellow=both). In this case study, MATLAB, the Image Processing and Signal Processing toolboxes were used to determine the green intensities from a small portion of a microarray image containing 4,800 spots. A 10x10 pattern of spots was detected by averaging rows and columns to produce horizontal and vertical profiles. Periodicity was determined automatically by autocorrelation and used to form an optimal length filter for morphological background removal. A rectangular grid of bounding boxes was defined. Each spot was individually addressed and segmented by thresholding to form a mask. The mask was used to isolate each spot from surrounding background. Individu)

说明：  QPSK详细调制解调的源码，包括整个流程．(QPSK modulation and demodulation of the source in detail, including the entire process.)