shexianzhuizong

用matlab实现了数字信号处理中的多采样样转换，并依此原理进行采样转换滤波器的设计。 (Multi-sampling samples converted digital signal processing using matlab, and so the principle of sampling conversion filter design.)

In wireless sensor network, residual energy of node is very important criteria. Life of wireless sensor network depend the energy of node. In most of the application, the nodes are battery operated. So it is very important to select the parameters like nodes deployment in network, size of packet, etc. In work,analyze node’s energy with respect to packet size, distance, time and also how much data can be transmitted. And finally we will conclude for the effective value of these parameters.

颜色处理类matlab工具箱，支持图像色度、亮度编辑，颜色分段等(Deal with category colors matlab toolbox to support the image chroma, brightness edit, and so the color sub-)

it presence the effect of stiffness variation in active air_suspension system.

本案例基于MATLAB的GUI工具进行设计仿真实验：通过对采集的车牌图像进行灰度变换、边缘检测、腐蚀及平滑等过程来进行车牌图像预处理，并由此得到一种基于车牌颜色纹理特征的车牌定位方法，实现车牌区域定位，最后实现车牌字符的分割与识别。(In this case based on MATLAB GUI design simulation tool: through the license plate image capture through gradation conversion, edge detection, corrosion and smoothing process for the license plate image preprocessing, and thereby obtain a color texture features based on license plate the method of license plate location, license plate positioning to achieve, and finally realize the segmentation and recognition of license plate characters.)

用Simulink仿真卷积编码，并用Viterbi译码的方法进行解码，其中的编解码全部自己编写代码(S-Function方式)(Simulink simulation using convolutional coding and Viterbi decoding method used to decode, which codec to prepare all their own code (S-Function mode))

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Numerically approximates the double integral of a standard bivariate Normal distribution

this is face recognition system in matlab

调用过程 CM = Confusion_matrix(train_predicts, train_targets) [combining_predicts, errorrate] = combining_NB(DP, test_targets, CM) DP，三维数组，(i,j,k)为第k个样本的DP矩阵 targets 为 0 1 2 (process called CM = Confusion_matrix (train_predicts, train_targets) [combining_predicts, errorrate] = combining_NB (DP, test_targets, CM) DP, three-dimensional array (i, j, k) for the k samples of DP matrix targets for 0 1 2 )