MATLAB(book)

System identification with adaptive filter using full and partial-update Normalised-Least-Mean-Squares

两电平SVPWM的MATLAB编程实现，输入端口为ＤＱ轴下的指令电压和直流侧电压，输出为开关函数的瞬时值(Two-level SVPWM the MATLAB programming, enter the port under the command DQ-axis voltage and DC voltage, the output for the switching function of the instantaneous value)

说明：  MATLAB实现kaiser窗函数。~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ (MATLAB kaiser window function to achieve)

本文提出一种新的智能故障诊断方法,基于统计分析,提出了一种改进的距离的评价技术和适应性类神经模糊推论系统(简称ANFIS)。该方法包括三个阶段。　(This paper presents a new approach to intelligent fault diagnosis based on statistics analysis, an improved distance evaluation technique and adaptive neuro-fuzzy inference system (ANFIS). The approach consists of three stages. First, different features, including time-domain statistical characteristics, frequency-domain statistical characteristics and empirical mode decomposition (EMD) energy)

This is a file two compute the angle between two target

There are different m files for different filter to use. perwit.m:=uses window Wx=[1 0 -1 1 0 -1 1 0 -1]/3 and Wy=Wx and then convolves this window with the image. sobel.m:=uses window W=[1 0 -1 2 0 -2 1 0 -1]/4 lablacian.m=uses window W=[0 1 0 1 -4 1 0 1 0] convolve.m=convolves window and image

定義如何槍在子彈內的運動規律之UDF，定義槍的構造以及邊界，設定槍的運動方式(UDF defines how the bullet in the gun law of motion, the definition of the structure and boundaries of the gun, the gun movement set)

说明：  This file contains Least Square method program which is one of en bloc approaches to identifying a system. The target is calculating parameter vector of a system

本光盘为《详解MATLAB快速入门与应用》一书的配套光盘，包括以下内容： 1.“sample”文件夹：提供了本书各章范例的源程序。(The CD is " Getting Started with MATLAB Detailed application," a book supporting the CD, including the following:. 1 " sample" folder: each chapter provides examples of the book source.)

说明：  该代码出自于2004年Coello的"Handling Multiple Objectives With Particles Swarm Optimization"这篇文章的源代码(this file is used to solve Multiple Objectives problems by pso in matlab)