First_Order

提取感兴趣区域的演示程序,有GDI界面的,方便实用.(Demo )

空间滤波，matlab编程，介绍了低通滤波器，带通滤波器和高通滤波器。(Spatial filtering, Matlab programming, low-pass filter, band-pass filter and high pass filter.)

EFFICIENT RANDOM VARIATES GENERATOR (from over 50 distributions):Alpha, Anglit, Antilognormal, Arcsin, Bernoulli, Bessel, Beta, Binomial, Bradford, Burr, Cauchy, Chi, Chi-Square (Non-Central), Chi-Square (Central), Cobb-Douglas, Cosine, Double-Exponential, Erlang, Exponential, Extreme-Value, F (Central), F (Non-Central), Fisher-Tippett, Fisk, Frechet, Furry, Gamma, Generalized Inverse Gaussian, Generalized Hyperbolic, Geometric, Gompertz, Gumbel, Half-Cosine, Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Laplace, Logistic, Lognormal, Lomax, Lorentz, Maxwell, Nakagami, Negative Binomial, Normal, Normal-Inverse-Gaussian (NIG), Pareto, Pareto2, Pascal, Planck, Poisson, Quadratic, Rademacher, Rayleigh, Rice, Semicircle, Skellam, Student s-t, Triangular, Truncated Normal, Tukey-Lambda, U-shape, Uniform (continuous), Von Mises, Wald, Weibull, Wigner Semicircle, Yule, Zeta,(EFFICIENT RANDOM VARIATES GENERATOR (from over 50 distributions): Alpha, Anglit, Antilognormal, Arcsin, Bernoulli, Bessel, Beta, Binomial, Bradford, Burr, Cauchy, Chi, Chi-Square (Non-Central), Chi-Square (Central), Cobb-Douglas, Cosine, Double-Exponential, Erlang, Exponential, Extreme-Value, F (Central), F (Non-Central), Fisher-Tippett, Fisk, Frechet, Furry, Gamma, Generalized Inverse Gaussian, Generalized Hyperbolic, Geometric, Gompertz, Gumbel, Half-Cosine, Hyperbolic Secant, Hypergeometric, Inverse Gaussian, Laplace, Logistic, Lognormal, Lomax, Lorentz, Maxwell, Nakagami, Negative Binomial, Normal, Normal-Inverse-Gaussian (NIG), Pareto, Pareto2, Pascal, Planck, Poisson, Quadratic, Rademacher, Rayleigh, Rice, Semicircle, Skellam, Student s-t, Triangular, Truncated Normal, Tukey-Lambda, U-shape, Uniform (continuous), Von Mises, Wald, Weibull, Wigner Sem)

The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter, but has better behaviors near edges. The guided filter is also a more generic concept beyond smoothing: it can transfer the structures of the guidance image to the filtering output, enabling new filtering applications like dehazing and guided feathering. Moreover, the guided filter naturally has a fast and non-approximate linear time algorithm, regardless of the kernel size and the intensity range. Currently it is one of the fastest edge-preserving filters.

仿真BPSK、QPSK、GMSK等基本调制方式。(Simulation BPSK, QPSK, GMSK modulation scheme.)

GM(1，N)模型的MATLAB实现,轻松实现GM模型的操作，且易于实现，很方便(MATLAB implementation of GM (1, N) model)

This program uses the timers to trigger EDMA events. These events in turn * trigger linked EDMA parameter tables to fill a ping pong buffer structure. * Set a breakpoint on swiProcessFunc(int arg). Then open two memory windows. * Use ping as the address for one memory window and pong for the other. Then * run the application. You ll note that the program bounces between the ping * and pong buffers filling each with a value that comes from the source. The * source in this case is the SDRAM timer control register and it simulates * input data(This program uses the timers to trigger EDMA events. These events in turn* trigger linked EDMA parameter tables to fill a ping pong buffer structure.* Set a breakpoint on swiProcessFunc (int arg). Then open two memory windows.* Use ping as the address for one memory window and pong for the other. Then* run the application. You' ll note that the program bounces between the ping* and pong buffers filling each with a value that comes from the source. The* source in this case is the SDRAM timer control register and it simulates* input data)

位置感知应用程序市场 位置估算技术 其它S60 平台运行时中的位置API 使您的应用程序感知位置时需要考虑的因素 协助测试的开发工具。(Location-aware applications market position estimation techniques other S60 platform run-time the position of the API to your application-aware location factors to be considered to help test the development tools.)

Fibonacci method is an optimization method which can be used to find optimum of a 1D function (even discrete function) using elimination method. For use this method the initial interval of uncertainty, in which the optimum lies, has to be known. In addition the objective function should be unimodal, which has just an optimum solution in initial interval.

Levinson算法估计功率谱的MATLAB源程序 含有不同参数情况下的功率谱曲线，含有仿真结果(Levinson algorithm to estimate the power spectrum MATLAB source code contains the power spectral curve, in the case of different parameters contains simulation results)