kongjianfenbusanweitu

Rake receiver with ds-ss

说明：  利用遗传算法优化BP神经网络权值和阈值，然后进行训练，利用训练好的模型进行预估。附实例(The use of genetic algorithm to optimize BP neural network weights and thresholds, and then training, training a good use of forecast models. Attached examples)

应用小波神经网络进行模式识别的MATLAB源程序(Wavelet neural network pattern recognition MATLAB source)

Illegal Format Code Point Exception extends Illegal Format Exception implements Serializable.

说明：  产生高斯白噪声并用不同方法求解其PSD（功率谱密度）(Generating Gaussian white noise and solving its PSD)

matlab/simulink simpowersystems (Three-phase_asynchronous_motor_reversal)

EM Numerical Modeling of a Monopole

这个程序是属于阵列信号处理范畴的，利用TLS-ESPRIT算法进行测向，是一个子程序，阵列形式可以是任意的，可以设置接收信号的模型，然后运用此算法测向。(This program belongs to array signal processing areas, the use of TLS-ESPRIT direction finding algorithm is a subroutine, the array can be any form, you can set a model the received signal, and then use this algorithm finding.)

brushless dc motor model

创建一个n维的稀疏数组对象，n是任意值。 定义N可能是大于2的一类n维稀疏阵列。然而，它应该被认为是一种起动方式与普通的MATLAB稀疏矩阵和重塑它有N维度。换句话说，稀疏的数据，首先必须能够作为一个普通的2D MATLAB稀疏矩阵被前n维。事实上，如果目标数组的尺寸mxnxp……yxz，然后将它存储在内部类是一个普通的二维稀疏阵列的尺寸（M×N×P×……×Y）XZ。这导致了某些内存株时使用大量的尺寸。我发现有用的类主要用于中等尺寸像三维图像边缘检测，你经常要举行一个稀疏的3D的边缘地图。(Creates an N-dimensional sparse array object, for arbitrary N.This submission defines a class of N-dimensional sparse arrays for N possibly greater than 2. However, it should really be thought of as a way of starting with an ordinary MATLAB sparse matrix and reshaping it to have N dimensions. In other words, the sparse data must first be able to exist as an ordinary 2D MATLAB sparse matrix before being made N-dimensional. In fact, if the intended array has dimensions MxNxP...YxZ, then the class will store it internally as an ordinary 2D sparse array of dimensions (M*N*P*...*Y)xZ. This leads to certain memory strains when using large numbers of dimensions. I find the class useful mainly for moderate dimensional things like edge detection in 3D imaging, where you often want to hold a sparse 3D edge map. )