demodulators

说明：  先进PID控制matlab仿真(第二版)源程序，作者：刘金琨，电子工业出版社，2004年9月第一次印刷。在控制方向十本不错的书，里面的控制算法很值得借鉴！(Matlab simulation of advanced PID control (second edition) source, Author: Liu Jinkun, Publishing House of Electronics Industry, in September 2004 the first printing. 10 in the control of the direction of a good book, which control algorithm is worth learning!)

入门级代码，matlab源代码的第二部分。(Entry-level code, matlab source code for the second part.)

说明：  小波分析 图像融合 决策树分类 matlab 源代码 (fusion image, classify)

说明：  《MATLAB 7.0编程基础基础》源程序，适合于初学者练习(&quot MATLAB 7.0 programming foundation base&quot source, suitable for beginners)

高阶谱分析包，应用范围包括阵列信号处理，盲源信号处理等(higher order spectral analysis package, including the application of array signal processing, blind signal processing)

LTSA[19] is based on the intuition that when a manifold is correctly unfolded, all of the tangent hyperplanes to the manifold will become aligned. It begins by computing the k-nearest neighbors of every point. It computes the tangent space at every point by computing the d-first principal components in each local neighborhood. It then optimizes to find an embedding that aligns the tangent spaces.

matlab下用FFT求功率谱和幅值谱的代码(Power spectrum and Amplitude spectrum base on matlab)

一种改进的萤火虫算法解决动态0-1背包问题。经过测试，算法就有良好的性能。(Firefly Algorithm (FA), Genetic Algorithm (GA) and Differential Evolution (DE) have been widely used for static optimization problems, but the applications of those algorithms in dynamic environments are relatively lacking. In the present study, an effective FA introducing diversity with partial random restarts and with an adaptive move procedure is developed and proposed for solving dynamic multidimensional knapsack problems. To the best of our knowledge this paper constitutes the first study on the performance of FA on a dynamic combinatorial problem. In order to uate the performance of the proposed algorithm the same problem is also modeled and solved by GA, DE and original FA. Based on the computational results and convergence capabilities we concluded that improved FA is a very powerful algorithm for solving the multidimensional knapsack problems for both static and dynamic environments.)

this document is paper

The classic hello.cpp