Wavelet

Jakes Simulation Models With Correct Statistical Properties for Rayleigh Fading Channels

This matlab simulation model explains operation of openloop Buckboost converter.

说明：  半导体数据训练集和测试集用来检测故障,使用MATLAB编程对数据采集(Semiconductor data training and test sets used to detect faults, using MATLAB programming for data collection)

运用高斯混合模型，识别车辆，分割车辆，检测车流量，运算很快，效果不错(Using the gaussian mixture model, identification of vehicles, vehicle segmentation, detection and traffic operation soon, effect is good)

这是一个相对完整的OFDM通信系统的仿真设计，包括编码，调制，IFFT，上下变频，高斯信道建模，FFT，PAPR抑制，各种同步，解调和解码等模块，并统括系统性能的仿真验证了系统设计的可靠性。 (This is a relatively complete simulation of OFDM communication system design, including coding, modulation, IFFT, the upper and lower frequency, Gaussian channel model, FFT, PAPR suppression, a variety of synchronization, demodulation and decoding module, and system performance omnibus simulation of the system reliability.)

主成分析matlab图形用户界面代码，包含测试文件。(principal component analysis matlab gui code. test file included.)

加性高斯噪声信道下BPSK信道估计，matlab程序，做得还比较好！希望能帮助你们！(AWGN channel under BPSK channel estimation, matlab procedure done better! To help you!)

This is a matlab project in which application detect the brain tumour.

针对离散系统进行开环、闭环分析；绘制Bode、Nyquist、根轨迹图；阶跃、脉冲响应，并均给出响应的图示。(For the discrete system closed loop analysis of ring, open drawing Bode, Nyquist, root locus diagram step, impulse response, and the response of the diagrams are given.)

遗传算法是计算机科学人工智能领域中用于解决最优化的一种搜索启发式算法，是进化算法的一种。这种启发式通常用来生成有用的解决方案来优化和搜索问题。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的，这些现象包括遗传、突变、自然选择以及杂交等。(In the field of artificial intelligence, a genetic algorithm (GA) is a search heuristic that mimics the process of natural selection. This heuristic (also sometimes called a metaheuristic) is routinely used to generate useful solutions to optimization and search problems.[1] Genetic algorithms belong to the larger class of evolutionary algorithms (EA), which generate solutions to optimization problems using techniques inspired by natural evolution, such as inheritance, mutation, selection, and crossover.)