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The model consists of two systems, a climate control system and an electrical system. This allows for examination of the loading effects of the climate control system on the car s electrical system.

一维和二维离散余弦变换的文件，通俗易懂。(This is for students who is major in communication project.)

speech compression using fft

Heart rate and QRS complex detection for ECG in MATLAB.

基于matlab的系统分析与设计之信号处理 源代码(MATLAB signal processing)

关于SAR和极化SAR信息处理的好程序。Cloude.m——经典的Cloude极化分解方法中H/alpha参数的求解方法；classes.m——Cloude极化分解方法；myCFAR.m——三种SAR图像目标检测的恒虚警处理方法。全局CFAR，局部CFAR，指数CFAR(SAR and POLSAR information processing codes. Cloude.m-- H/alpha parameter ofclassic Cloude polarization decomposition classes.m--Cloude decomposition myCFAR.m-- the three CFAR methods of target detection in SAR images)

包括：用基本粒子群算法求解无约束优化问题，用带压缩因子的粒子群算法求解无约束优化问题，用线性递减权重粒子群优化算法求解无约束优化问题，用自适应权重粒子群优化算法求解无约束优化问题，用随机权重粒子群优化算法求解无约束优化问题，用学习因子同步变化的粒子群优化算法求解无约束优化问题，用学习因子异步变化的粒子群优化算法求解无约束优化问题，用二阶粒子群优化算法求解无约束优化问题，用二阶振荡粒子群优化算法求解无约束优化问题(Include: using the particle swarm algorithm for unconstrained optimization problems, with compression factor of particle swarm algorithm for solving unconstrained optimization problem with linear decreasing weight particle swarm optimization for unconstrained optimization problems, an adaptive weight particle swarm optimization unconstrained optimization problems, random weight particle swarm optimization algorithm for unconstrained optimization problems, with the learning factor synchronous change of particle swarm optimization algorithm for unconstrained optimization problems, with the learning factor asynchronous changes in particle swarm optimization algorithm for solving unconstrained optimization problem , with the second particle swarm optimization for unconstrained optimization problems, with the second-order oscillating particle swarm optimization algorithm for unconstrained optimization problem)

用于模式识别分类，有C均值算法、HK算法以及感知器算法(for the classification, C-means algorithm, HK algorithm and Perceptron Algorithm)

为了对数据进行准确的预测，建立了双隐层BP神经网络，并提供了源数据，实现了准确的数据预测。程序能够执行，误差较小，输出接近真实值。(To accurately forecast the data, we build the two-hidden layer BP neural network and provide the original data, which will forecast the data. The program can be executed with small error which will be close to the real data.)

synchronously rotating model of induction motor