pudn_psw

详细介绍了混沌粒子群算法，并且进行程序的编写，里面还有7篇混沌粒子群的论文(Detailed introduces the chaotic particle swarm algorithm, and the writing of the procedures, inside still have 7 article chaotic particle group of papers)

DF schemes provide better performance than the AF schemes. However DF schemes are more computationally intensive at the RS. Also transmit diversity seems to perform better than receive diversity. However receive diversity does not need the BS to transmit during the second phase. Hence it can schedule another user in this slot. The benefit of receive diversity will be visible when we do network simulations

This source code for calculate of element of satellite.

本代码解决的是在线性高斯环境下的目标跟踪，给出的是势均衡多目标多伯努利滤波器的高斯混合实现，本代码能够正常运行。( This code is to solve linear Gaussian target tracking environment, Gaussian mixture is given multi-objective multi-bonuli potential equalization filter implementation, this code to run properly.)

最近在书上找的一个程序，可以对微分方程的解法使用(Themselves in line to see a square root to be evaluated on, you can refer to the following)

多重分形领域中Hurst指数的计算及主程序运行(Multifractal field Hurst exponent calculation and main run)

直线开关磁阻电机直接力矩控制仿真，其中的磁链开关表部分不是特别完整(Linear switched reluctance motor direct torque control simulation)

Training Artificial Neural Network. XOR Problem. Summation Units, Log-Sigmoid Neurons with Biases. Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons. Returns mean square error between desired and actual outputs. Reference Papers: D. Karaboga, B. Basturk Akay, C. Ozturk, Artificial Bee Colony (ABC) Optimization Algorithm for Training Feed-Forward Neural Networks, LNCS: Modeling Decisions for Artificial Intelligence, 4617/2007, 318-329, 2007. D. Karaboga, C. Ozturk, Neural Networks Training by Artificial Bee Colony Algorithm on Pattern Classification, Neural Network World, 19(3), 279-292, 2009. */

这是对于雷克子波的处理过程，是对地震子波处理的缩写版(This is for the Ricker wavelet processing, seismic wavelet processing is the abbreviated version of)

A Gabor-filtering method for describing textural features is proposed, which applies the physical properties of a probability wave to probability transformation, and computes textural features 2) An adaptive strategy for feature and filter selection, and feature weighting, is proposed, which utilizes a user’s relevance feedback to reduce the redundancy in the representation and incorporate the user’s information needs in image retri 3) Integrating both schemes (the Gabor-filtering method and the adaptive strategy) for content-based mammogram retri is suggested