chap10

plots a 3-D "line" with c-data as color Makes a surface object and the colouring is controlled by the colormap.

a simple implementation for 4 16 64 QAM plots to obtain simulated and theoretical results for OFDM system

对两幅图片进行无缝融合，使用的是泊松原理，融合效果优秀(For seamless integration of two images, using a Poisson principle, excellent fusion effect)

说明：  多步最小二乘法程序，适用与利用MATLAB进行系统辨识计算(Multi-step least squares procedure, applied to system identification using MATLAB calculation)

用matlab实现雷达信号的卡尔曼滤波的仿真(Of radar signals using matlab simulation of the Kalman filter)

针对二维熵图像分割方法在求取最佳阈值时存在计算量大及微粒群算法容易陷 入局部最优且速度较慢等等问题, 提出了基于混沌粒子群优化算法的二维熵图像分割方法。 该方法考虑了图像中像素点灰度􀀂 􀀂 􀀂 邻域灰度均值对作为阈值对图像进行分割 利用混沌运 动随机性、遍历性和初值敏感性, 将混沌粒子群优化算法与阈值法相结合在二维空间作全局搜 索。实验结果表明了基于混沌粒子群优化算法的二维熵图像分割法用于阈值寻优减少了搜索 时间, 提高了收敛率。(Calculation of its large capacity and particle swarm algorithm is easy to fall to strike the best threshold for the two-dimensional entropy image segmentation method Into the local optimum and slower, the proposed two-dimensional entropy image segmentation method based on chaotic particle swarm optimization algorithm. The method takes into account the image pixel the gray 􀀂 􀀂 􀀂 neighborhood average gray value as a threshold for image segmentation chaotic transport Dynamic randomness, ergodicity and initial value sensitivity of chaotic particle swarm optimization algorithm with the threshold method in two-dimensional space for the global search On request. Experimental results show that the entropy method of image segmentation method based on chaotic particle swarm optimization algorithm for threshold optimization to reduce the search Time and improve the convergence rate.)

自相关函数在噪声检测,识别和有用信号的提取中的应用(autocorrelation function of the noise detection, identification and extraction of the useful signal of)

this code makes the weka tool accepts arabic language

XXY 平台移動計算,利用三點位置算出中心進行偏移動作(XXY mobile computing platform using three shift operation center position calculating)

现有的PID参数优化方法往往难以同时兼顾系统对快速性、稳定性与鲁棒性的要求，本文针对这一缺陷，提出了一种多目标PID优化设计方法——在满足系统的鲁棒性的前提下，以超调量、上升时间和调整时间最小作为多目标优化的子目标，并将NSGA-Ⅱ与PGA相结合对其求解。该算法求得的Pareto最优解分布均匀，收敛性和鲁棒性好，决策者可根据实际系统的要求在Pareto解集中选择最终的满意解，这为快速性、稳定性与鲁棒性的权衡分析提供了有效的工具。仿真结果表明本文设计方法的有效性和优越性。()