wireless_communication

这是一篇很好的有关信道估计的文章， 可以用来快速的了解信道估计的基本内容(and MAI induced by multiple-input, multiple-output channels. In particular, this article reviews the typical inverse filter criteria (IFC) based algorithm, super-exponential algorithm, and constant modulus algorithm along with their relations, performance, and improvements. Several advanced applications of these algorithms are illustrated, including blind channel estimation, simultaneous estimation of multiple time delays, signal-tonoise ratio (SNR) boost by blind maximum ratio combining, blind beamforming for source separation in multipath, and multiuser detection for direct sequence/code division multiple access (DS/CDMA) systems in multipath.)

關於語音辨識的一些程序樣例用matlab語言編程(some of example program about speech recognization in matlab)

说明：   提供的文件包含matlab的多个图象处理程序,其中有图象分割,以及图象边缘提取的.(the document contains a number of Matlab image processing procedures, which are image segmentation, and Image Edge Extraction.)

通过对语音的读入，对起进行语谱分析，以前，接着对语音进行了基音的提取，对语音进行分析！(Through the voice to read the language have been carried out spectral nalysis, in the past, followed by a pitch on the voice of the extraction, analysis of the audio!)

求解约束优化，非线性最小二乘优化，线性优化，整数规划，二次规划等最优化问题(Solving constrained optimization, nonlinear least squares optimization, linear optimization, integer programming, quadratic programming and other optimization problems)

说明：  小波包分解程序，小波基函数db5进行三层分解(Wavelet packet decomposition program, wavelet basis function db5 for three-level decomposition)

说明：  根据自适应模糊控制原理，设计自适应律，并设计simlink主程序和控制器S函数，对机器人单臂机械手进行自适应模糊控制。(fuzzy adaptive control )

电机的电压矢量控制方法的仿真，有做电机控制的，尤其是交流电机的，可以看看 (motor voltage vector control method of simulation, so the motor control, in particular the AC motor can see)

PCM通信系统脉冲编码调制的信源编码，可以运行。模拟PCM的编码的波形！(PCM communication system pulse code modulation source coding, can run. Simulation of the PCM waveform coding!)

2D version of Brownian motion. A random walk is similar to markov process, however a markov process has no memory, where a random walk uses an initial state. The next step in the walk does not necessarily depend on your current state but will be referenced from your current state, that is to say the random vector is added to your current state. depending on complexity