Matlab扩展编程

说明：  将粒子群算法与免疫结合，计算函数的优化极值。(The particle swarm optimization combined with the immune calculated extremal function optimization.)

BP 神经网络算例，很好的算例程序，希望对大家有帮助(BP neural network example, the example program, we hope to help)

Good paper for a research about the field of medical.

某石油公司计划建造一条由东向西的主输油管道。该管道要穿过一个有n 口油井的油田。从每口油井都要有一条输油管道沿最短路经(或南或北)与主管道相连。如果给定n 口油井的位置,即它们的x 坐标（东西向）和y 坐标（南北向）,应如何确定主管道的最优位置, 即使各油井到主管道之间的输油管道长度总和最小的位置?证明可在线性时间内确定主管道的最优位置。(An oil company plans to construct a east to west from the main pipeline. The pipeline to pass through an oil field n wells. Wells from each must have a pipeline along the shortest path (or South or North) connected with the competent Road. If given the location of oil wells in n, that is, their x coordinates (east-west) and y coordinates (north-south), should be how to determine the optimal position in charge of Road, even if the wells to the pipeline in charge of Road between the sum of the smallest length location? proved to be linear time to determine the optimal position in charge of Road.)

This is a morpholog methods that process an image with (Dialion, Erosion, open , close ,,etc)

solution of d satacom in system in transimation line by compensatin

一个身体部位比较模型的新方法网络（BAN）的，可以容纳多个环节和多个科目。所述的绝对测量允许跨频谱可能刻画的比较 从单参数为整个合奏，通过基于参数化到每个活动，每个学科和每个环节模型。使用错误，并明确之间权衡复杂性，在一个善良的适应措施相结合，显示有重要的影响时，适用于一系列典型的禁止通道数据。它是有不同的 在模式的选择的影响，以及它相关的复杂性，混合活动的“日常”的数据，设置活动相比，动态数据（例如步行）。平均路径损耗的不足，甚至位数的路径损失的措施，作为唯一的表征还强调“禁止通道。 (A new approach to compare models for body area networks (BAN) that accommodates multiple links and multiple subjects is presented. The absolute measure described allows comparison across a spectrum of possible characterizations ranging from single-parameter for an entire ensemble, through to per-activity, per-subject and per-link based parameterized models. The use of an explicit trade-off between error and complexity, combined in a goodness-of-fit measure, is shown to have important consequences when applied to a range of typical BAN channel data. It is shown that there are different implications in choice of model, and it’s associated complexity, for mixed-activity “everyday” data, when compared with set-activity dynamic data (e.g. walking). The deficiency of mean path loss, or even median path loss measures, as a sole characterization of the BAN channel is also highlighted.)

ica_filter for signals matlab code

详细的卷积编码与维特比译码算法。产生随机信号，对信号进行卷积编码，然后经过数值转换、格雷编码，QPSK调制，进入加噪信道，之后进行QPSK解调，格雷解码， 数制转换、 维特比译码得到接收端的信号。(Detailed convolutional coding and Viterbi decoding algorithm. Random signal, the signal convolution coding, and then through numeric conversion, Gray coding, QPSK modulation, plus noise into the channel, followed by QPSK demodulation, decoding Gray, number system conversion, Viterbi decoding to get the receiving end of the signal.)

自己写的一个关于chase算的程序，能得到最后的译码结果。主要用于乘积码和广义LDPC的译码算法上，有较好的性能。(Write a program to calculate on the chase, will be the final decoding results. Mainly used for product codes and generalized LDPC decoding algorithm, there is better performance.)