toolbox_signal

内含用神经网络进行信号处理的两个实例，采用MATLAB编写。(Intron with neural network signal processing of two examples of using MATLAB to prepare.)

simulation of robot manipolator

Dan Simon, Training radial basis neural networks with the extended Kalman Filter, 2001. Article on RBF neural networks, with examples, source programs on Matlab

Matlab code for Fluid Replacement Modelling

The same staff as before.

for image registration and vision, GPS

Lead-Acid Battery This demo implements a model of a lead-acid battery cell using the Simscape™ language to implement the nonlinear equations of the equivalent circuit components. In this way, as opposed to modeling entirely in Simulink® , the connection between model components and the defining physical equations is more easily understood.

This Matlab Code models a Rayleigh fading channel using a modified Jakes channel model. A modified Jakes model chooses slightly different spacings for the scatterers and scales their waveforms using Walsh–Hadamard sequences to ensure zero cross-correlation. alpha_n = frac{pi(n-0.5)}{2M} and eta_n = frac{pi n}{M}, results in the following model, usually termed the Dent model or the modified Jakes model: R(t,k) = sqrt{frac{2}{M}} sum_{n=1}^{M} A_k(n)left( cos{eta_n} + jsin{eta_n} ight)cos{left(2pi f_d t cos{alpha_n} + heta_{n} ight)}. The weighting functions A_k(n) are the kth Walsh–Hadamard sequence in n. Since these have zero cross-correlation by design, this model results in uncorrelated waveforms. The phases ,! heta_{n} are initialized randomly and have no effect on the correlation properties. Matlab fast Walsh-Hadamard transform function is used to efficiently generate samples using this model.

Matlab allows the use of MEX files –MEX files are pre-compiled files that are called from Matlab –Can be compiled from Matlab .m files –Can also be compiled from external C++ code. • This will be our focus

用MATLAB 实现的综合云模型的实现。很有意思和参考价值(Implemented with the MATLAB implementation of comprehensive cloud model. Very interesting and valuable)