pmsys

对机械振动信号的预处理，以及滤波，频域变换等(The pretreatment of the mechanical vibration signal, and filtering, frequency domain transform, etc.)

详细介绍了Simulink工具箱，对于系统仿真很有用(Details the Simulink toolbox it is useful for system simulation)

基于EMD的Hilbert-huang变换(Hilbert-huang transform based on EMD)

Ecg beat detection in matlab

A sound source can be localized in a two dimensional plane using the audio recorded at three known microphone locations. Much like a GPS system, Time Difference of Arrival algorithms can be used to determine the difference in time and distance of a sound source to other microphones. With that information a Chan algorithm can be used to determine the X Y coordinates of the originating sound source. To do so, however, you must first provide the XY coordinates of each of the 3 microphones. Note that for faster and simpler calculation one of the microphones should be placed at the origin (0, 0) of you XY plane.

程序包括EFICA，WASOBI及两者的结合，可以快速实现盲源分离。(The program includes EFICA, WASOBI and their combination, can quickly achieve blind source separation.)

A multi-target tracking toolbox based on the MTT Library of the InstantVision ISE with expanded functionality and tools for off-line design, analysis and testing. The toolbox contains the implementation of distance calculation methods (e.g. city-block based), data assignment and association strategies (e.g. ENN and JVC), state prediction filters (e.g. IMM) with video marking and debugging tools in order to support a complex multi-target tracking system design.

蔡氏混沌电路的控制，主要有线性控制，非线性控制，微分控制，等其他控制，完整的程序和方程。(Chaotic circuit control, linear control, nonlinear control, differential control, and other control, complete the procedures and equations.)

MATLAB教材学习资料MATLAB教材学习资料MATLAB教材学习资料MATLAB教材学习资料(studying for matlab)

这个例子展示了如何应用偏最小二乘回归(plsr)和主成分回归(PCR),并讨论了两种方法的有效性。 本人亲测有效(This example shows how to apply Partial Least Squares Regression (PLSR) and Principal Components Regression (PCR), and discusses the effectiveness of the two methods. PLSR and PCR are both methods to model a response variable when there are a large number of predictor variables, and those predictors are highly correlated or even collinear. Both methods construct new predictor variables, known as components,)