delay

说明：  根据过完备原子库中原子的能量分布特性创建大小原子的Matlab程序。(Over-complete atoms according to the Treasury in the distribution of atomic energy to create the size of atoms Matlab procedures.)

本源码将横向自适应滤波器和格型自适应滤波器的LMS算法综合在一起,对起权系数跟踪性能可以做较好的比较(The source transverse adaptive filter and adaptive lattice filter LMS algorithm combined starting weight coefficient tracking performance can do a better comparison)

从0开始移植UCOS II到STM32开发板，十分详细的资料，讲的很清楚。手把手教学(From 0 to the UCOS II to STM32 development board, very detailed information, very clear. Hand handle teaching)

viterbi algorithm in matlab simulation

Matlab的FFT算法程序 里面有基2时间抽取的FFT 还有基2频率抽取的FFT (Matlab' s FFT algorithm which has taken the time base 2 radix-2 FFT have taken the FFT frequency)

基于Matlab的仿真,虚拟信号发生器,实现各种信号(sin cos ... )的发生(Matlab based simulation, virtual signal generator based on Matlab simulation, virtual signal generator, achieve various signals (sin...The occurrence of))

matlab之语音处理与合成工具箱的随书程序！！！Good!!!It s useful for you !!!(Good!!!It s useful for you !!!)

log5pitch : 将Hz为单位的基频转换为五度标记法规定的声调，先传入四个声调的基频，然后输出四个声调的五度值 myExcelWrite : 用matlab向Excel表单中写入内容(log5pitch: the fundamental frequency in Hz is converted to five times the tone mark law, passed in the first four tones of the fundamental frequency, then the output value of four tones of the five degrees myExcelWrite: using matlab to write content to an Excel spreadsheet)

Code matlab for wireless sensor networks

An important aspect of an ANN model is whether it needs guidance in learning or not. Based on the way they learn, all artificial neural networks can be divided into two learning categories - supervised and unsupervised. • In supervised learning, a desired output result for each input vector is required when the network is trained. An ANN of the supervised learning type, such as the multi-layer perceptron, uses the target result to guide the formation of the neural parameters. It is thus possible to make the neural network learn the behavior of the process under study. • In unsupervised learning, the training of the network is entirely data-driven and no target results for the input data vectors are provided. An ANN of the unsupervised learning type, such as the self-organizing map, can be used for clustering the input data and find features inherent to the problem.