dsp_mark

该程序是基于小波变换的熵谱，用来提取时间序列的周期成分。熵谱相对于小波谱来说在提取周期成分上有一定优势(The program is based on spectral entropy of wavelet transform to extract time series of the periodic component. Entropy is relative to the small spectral component in the extraction cycle, there are some advantages)

matlab开发的非绝热毛细管流动过程的模拟(Matlab development of the non-adiabatic capillary flow simulation)

利用共振解调，分析齿轮和轴承的信号，找出故障频率，此为源代码。(Using the resonance demodulation analysis the gear and bearing signals to identify the frequency of failure, this is the source code.)

两种图像重建质量判定方法，全图熵（ENT）和目标杂波比（Target to clutter ratio）。(Two criterion for image reconstruction,full image entropy and target to clutter ratio)

I have often found that user input edit boxes on a dialog require much more than the capabilities provided by the basic CEdit control. A common problem I have encountered is the need for an edit control that restricts the characters that can be entered into the box in some manner. Some types of restrictions would include confining input to a specific set if legal characters, excluding characters in an illegal set, limiting text to a maximum length and providing for fixed length strings that may be padded to the right with spaces if they are too short.

《空间谱估计原理与算法》多重信号分类法估计matlab源代码(" Space Spectrum Estimation Principle and Algorithm" multiple signal classification method estimates matlab source code)

TD中扩频的链路级仿真 通过MATLAB实现(TD Spreading the Link Simulation through MATLAB)

对点目标的回波进行了仿真，该仿真可以帮助大家对雷达的回波有更深一步的认识(Point target echo simulation, the simulation can help to have a deeper understanding of the radar echo)

在MATLAB环境下用经典参数法求高斯信道的参数(In the MATLAB environment parameters method with the classical Gaussian channel parameters)

线性预测分析是最有效的语音分析技术之一，在语音编码、语音合成、语音识别和说话 人识别等语音处理领域中得到了广泛的应用。语音线性预测的基本思想是：一个语音信号的 抽样值可以用过去若干个取样值的线性组合来逼近。通过使实际语音抽样值与线性预测抽样 值的均方误差达到最小，可以确定唯一的一组线性预测系数。(Linear predictive analysis is one of the most effective voice analysis technology has been widely applied in the field of speech processing speech coding, speech synthesis, speech recognition and speaker recognition and the like. The basic idea of ​ ​ linear prediction of speech is: a voice signal sample values ​ ​ can be approximated by a linear combination of a plurality of sample values ​ ​ of the past. By making the actual speech sample mean square error of the value of the smallest linear prediction sample values, to determine a unique set of linear prediction coefficients.)