matlabddfz

SOR FOR MATLAB NOT QUITE CORRECT BUT EASY TO UNDERSTAND

面向对象程序设计实验代码，此代码属于基础代码。(Experimental object-oriented programming code, this code belongs to the underlying code.)

关于单位根检测的matlab代码，有详细使用说明(Unit root test on the matlab code, detailed instructions)

用matlab计算了一种弹簧的刚度，以及进行了线性回归(failed to translate)

Softmax 函数处理，softmax 用于 Deep Learning 后的分类器的实现与识别，此函数的参数经过优化，有较强的泛化能力和性能(Softmax function processing, softmax classifier Deep Learning for the realization and recognition, the parameters of this function is optimized, there is a strong generalization ability and performance)

实现了高斯白噪声的信道模型，提供了相关的源代码(realize the model of a signal path)

snrz.m 本函数实现将输入的一段二进制码编为相应的单极性非归零码输出 snr.m 本函数实现将输入的一段二进制码编为相应的单极性归零码输出 dnrz.m 本函数实现将输入的一段二进制码编为相应的双极性非归零码输出 dnr.m 本函数实现将输入的一段二进制码编为相应的双极性归零码输出(snrz.m achieve this function the input of a binary code compiled for the corresponding unipolar NRZ output snr.m functions for the input of the binary code compiled for the corresponding period of the unipolar NRZ output dnrz.m The functions for the input of a binary code compiled for the corresponding bipolar NRZ output dnr.m achieve this function the input of a binary code compiled for the corresponding output bipolar RZ)

Speech Recognition - Numbers 1 to 5 Energy normalization and time alignment References: [1] L. Rabiner and B.H. Juang,Fundamentals of Speech Recognition, Prentice-Hall, 1993. ％ [2] P.E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. ％ [3] J.D. Markel and A.H. Gray,Linear Prediction of Speech(Speech Recognition-Numbers 1 to 5 Energy n ormalization and time alignment References : [1] L. Paras and B. H. Juang, Fundamentals of Speech Recognition. Prentice-Hall, 1993. % [2] P. E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. % [3] J. D. Markel and A. H. Gray, Linear Prediction of Speech)

Sound file processing using Matlab

改程序将实现对两个信号的曼切斯特编码，以用仿真软件验证过了(Reform program will achieve two Manchester encoded signal to a validated using simulation software)