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[Other resourcekalman_C

Description: 离散随机线性系统的卡尔曼滤波。 其中13lman.c是卡尔曼滤波函数,4rinv.c是滤波函数中用到的矩阵求逆函数,13lman0.c是主程序。-discrete stochastic linear Kalman filtering system. 13lman.c which is the Kalman filter function, 4rinv.c filtering function is used in the matrix inversion function, is the main program 13lman0.c.
Platform: | Size: 2059 | Author: 通信学生 | Hits:

[Data structskalman_C

Description: 离散随机线性系统的卡尔曼滤波。 其中13lman.c是卡尔曼滤波函数,4rinv.c是滤波函数中用到的矩阵求逆函数,13lman0.c是主程序。-discrete stochastic linear Kalman filtering system. 13lman.c which is the Kalman filter function, 4rinv.c filtering function is used in the matrix inversion function, is the main program 13lman0.c.
Platform: | Size: 2048 | Author: 通信学生 | Hits:

[matlabTheWholeDescriptionOfSimulinkStudy

Description: 以Simulink为主要工具介绍了系统仿真方法与技巧,包括连续系统、离散系统、随机输入系统和复数系统的仿真。介绍了模声封装技术、电力系统模块集、非线性系统设计模块集、S-函数编写与应用、Stateflow有限状态机、虚拟现实工具箱等中高级使用方法,最后还介绍了半实物仿真技术与实时控制技术。-Simulink as the main tool to introduce a system simulation methods and techniques, including continuous systems, discrete systems, stochastic input system and the simulation of complex systems. Introduce a sound module packaging technology, power system module set, non-linear system design blockset, S-function of the preparation and application, Stateflow finite state machine, virtual reality and other high use of the toolbox, and finally also introduce a semi-physical simulation technology and real-time control technology.
Platform: | Size: 605184 | Author: 阳关 | Hits:

[Algorithmoutput_feedback_stochastic_ode45

Description: 实现非线性、随机系统的输出反馈,针对的是单个系统。-To achieve non-linear, stochastic system with output feedback, is aimed at a single system.
Platform: | Size: 1024 | Author: 韩利霞 | Hits:

[matlabContemporary_MATLAB

Description: 现代通信系统(MATLAB版)(第二版)刘树棠译 本书系Brooks/Cole出版公司(Thomson Learning出版集团的下属子公司)2000年推出的BookWare系列丛书(BookWare Companion SeriseTM)之一种。该书提供了利用MATLAB的普及型学生版本在计算机上解决“现代通信系统”这门课程中涉及的几乎所有方面的问题的分析思路、方法、MATLAB脚本文件和处理结果的范例以及供学生自主学习研讨的习题。全书内容分为9章,分别是:信号与线性系统;随机过程;模拟调制;模拟/数字转换;基带数字传输;带限信道的数字传输;载波调制的数字传输;信道容量和编码;扩频通信系统。 -This book Brooks/Cole Publishing (Thomson Learning Publishing Group, a subsidiary) in 2000 launched BookWare Series (BookWare Companion SeriseTM) of a kind. The book provides the advantage of the popularity-based student version of MATLAB on the computer to solve the " modern communications systems," This course covered almost all aspects of the analysis of ideas, methods, MATLAB script files and processing the results of examples, as well as independent study for students seminar to answer. The book consists of nine chapters, namely: Signal and Linear System stochastic process analog modulation analog/digital conversion base-band digital transmission band-limited channel digital transmission carrier modulation digital transmission channel capacity and coding spread-spectrum communication systems.
Platform: | Size: 13392896 | Author: jiajunxian | Hits:

[Mathimatics-Numerical algorithmsKalmanMatlab

Description: 稳态kalman滤波算法仿真通式 本程序考虑线性离散时不变随机系统。系统模型为x(t+1)=fai*x(t)+gama*w(t) y(t)=H(t)*x(t)+v(t)。有6个参数:状态转移阵fai,输入噪声系数gama,观测阵H,输入 噪声方差Q,观测噪声方差R,观测y- Steady-state kalman filtering algorithm simulation program to consider the general form linear discrete time-invariant stochastic system. System model x (t+1) = fai* x (t)+ gama* w (t) y (t) = H (t)* x (t)+ v (t). There are six parameters: state transition matrix fai, input noise figure gama, observation matrix H, enter noise variance Q, observation noise variance R, observation y
Platform: | Size: 1024 | Author: 石志强 | Hits:

[matlabH-fliter

Description: 基于方差约束 ,研究一类不确定线性定常随机离散系统的 H ∞滤波问题。提出了一种 鲁棒滤波的新算法 ,该算法克服构造对角矩阵约束性较强- H ∞filtering problem under the constraint of variance was discussed for a class of linear stochastic uncertain system. A new algorithm of robust filter design was proposed which avoids strict constraint in constructing diagonal matrix to meet upper bound of variance. The robust filter with both constraints of variance and H ∞was given based on linear matrix inequality (LM I)
Platform: | Size: 182272 | Author: 李静 | Hits:

[matlablearn_kalman

Description: LEARN_KALMAN Find the ML parameters of a stochastic Linear Dynamical System using EM.
Platform: | Size: 2048 | Author: 李松寒 | Hits:

[matlabjitterbug-1.23

Description: JITTERBUG 是一个用来仿真线性控制系统的Matlab工具箱。通过JITTERBUG,我们能得到延时、数据丢失对系统的性能影响。同时,这个工具箱还能计算控制系统中信号的谱密度。-JITTERBUG [Lincoln and Cervin, 2002] is a MATLAB-based toolbox that allows the computation of a quadratic performance criterion for a linear control system under various timing conditions. Using the toolbox, one can easily and quickly assert how sensitive a control system is to delay, jitter, lost samples, etc., without resorting to simulation. The tool is quite general and can also be used to investigate jitter-compensating controllers, aperiodic controllers, and multi-rate controllers. As an additional feature, it is also possible to compute the spectral density of the signals in the control system. The main contribution of the toolbox, which is built on well-known theory (LQG theory and jump linear systems), is to make it easy to apply this type of stochastic analysis to a wide range of problems.
Platform: | Size: 35840 | Author: 钱三强 | Hits:

[matlablearn_kalman

Description: the ML parameters of a stochastic Linear Dynamical System using EM. -the ML parameters of a stochastic Linear Dynamical System using EM.
Platform: | Size: 2048 | Author: ilker | Hits:

[matlabContemporaryCommunicationSystems

Description: 本书提供了MATLAB在计算机上解决“现代通信系统”课程中涉及的个方面问题,分别讨论了信号与线性系统、随机过程、模拟调制、模拟数字转换、基带数字传输、数字传输、信道容量和编码、扩频通信系统等-The book provides MATLAB on the computer to solve the course of modern communication systems involved in aspects were discussed in signals and linear systems, stochastic processes, analog modulation analog to digital conversion, baseband digital transmission, digital transmission channel capacity and coding, spread spectrum communication system, etc....
Platform: | Size: 13321216 | Author: yang | Hits:

[OtherOptimization-method

Description: 详细的讲解最优化内容,包括:绪论,变分法,极大值原理,动态规划,离散时间系统,线性二次型,随机系统最优化。-The detailed explanation optimization content, including: introduction, variational method, maximum principle, dynamic programming, discrete-time systems, linear quadratic stochastic system optimization.
Platform: | Size: 1076224 | Author: yrb | Hits:

[Windows DevelopKalman

Description: 离散线性随机系统Kalman滤波,对问题进行了描述,分析并提出解决方案,并附加了相应程序-Discrete linear stochastic system Kalman filter, a description of the problem, analyze and propose solutions, and attach the appropriate procedures
Platform: | Size: 205824 | Author: 张子龙 | Hits:

[OtherCommunication-System-Simulation-1-2

Description: 通信系统仿真介绍的前面两章节的内容,讲述信号与线性系统和随机过程-Communication system simulation introduced in the previous two chapters, about the signals and linear systems and stochastic processes
Platform: | Size: 988160 | Author: K | Hits:

[Otherspectrem

Description: 清华张旭东老师《离散随机信号处理》教材第5章。本章首先简要复习经典谱估计的基本结论,然后分别讨论基于线性系统模型和复正弦模型的功率谱估计方法。-Qinghua Zhang Xudong teacher " discrete stochastic signal processing" textbook Chapter 5. This chapter begins with a brief review of the classical spectral estimation basic conclusion, and then discuss the power spectrum estimation based on linear system models and complex sinusoidal model approach.
Platform: | Size: 1508352 | Author: 吴丹 | Hits:

[Program docReview_math2

Description: 通信信号处理需要的基本数学知识,包括线性代数、Z变换、线性系统、统计特性等等。-digital signal processing in commnication system require some mathematical prelinaries including linear algebra,Z transform, linear system and stochastic process.
Platform: | Size: 203776 | Author: hanyu | Hits:

[matlabchapter1

Description: 连续时间切换线性随机系统稳定最小驻留时间搜寻程序-Continuous-time switched linear stochastic system is stable minimum dwell time of the search procedures
Platform: | Size: 2048 | Author: 黄冉 | Hits:

[MultiLanguageImproved_SMCPHD

Description: 该算法基本思想是利用一组带有相应权值的随机样本即粒子去逼近PHD分布和基数分布,其意义在于不仅解决重积分计算没有闭式解的难题,而且在滤波过程中,PHD函数被一系列离散的带权值的样本近似,随着样本粒子数量的增加,PHDF接近于Bayes最优估计,而且不受模型线性和高斯假设的限制,可以适用于非线性非高斯的随机系统。-The algorithm the basic idea is to use a set of random sample with the corresponding weight namely particle approximation PHD and base distribution, its significance lies in not only solve the problem of multiple integral calculation without closed solution, and in the process of filtering, PHD function by a series of discrete weighted value of sample approximation, with the increase of sample particles, PHDF close to the Bayes optimal estimation, and is not subject to the assumptions of the linear and gaussian model can be applied to nonlinear non-gaussian stochastic system.
Platform: | Size: 2048 | Author: lihua | Hits:

[source in ebookModern-communication-system

Description: 该资料现代数字通信及书中案例源码。 该书提供利用MATLAB的解决现代数字通信中涉及的几乎所有方面的问题的分析思路、方法、matlab脚本文件和处理结果案例以及学生自主研讨习题。全书分为9章。分别是:信号与线性系统、随机过程、模拟调制、模拟/数字转换、基带数字传送、带线信道的数字传送、载波调制的数字传输、信道容量和编码、扩频通信系统。-The modern digital communication data source and book cases. The book provides the use of MATLAB to solve the problem in almost all aspects of modern digital communication involved in the analysis of ideas, methods, matlab script file and the results of the case and deal with students' independent research exercises. The book is divided into nine chapters. They are: signal and linear systems, stochastic processes, analog modulation, analog/digital conversion, baseband digital transmission, digital transmission belt line channel, digital transmission carrier modulation, channel capacity and coding, spread spectrum communication system.
Platform: | Size: 8260608 | Author: 伍敏 | Hits:

[OtherOptimalstateestimation

Description: 最优状态估计与系统辨识 出版社:西北工业大学出版社 作者:王志贤 本书系统地阐述了最优状态估计与系统辨识的基本概念、基本理论和基本方法。全书共分两篇14章:第一篇为最优状态估计,分别介绍了最优估计的基本概念、线性系统的卡尔曼滤波、最优线性平滑、卡尔曼滤波的稳定性、滤波的发散及其克服方法、非线性滤波。第二篇为系统辨识,分别介绍了系统辨识的一般概念、脉冲响应法和相关函数法、最小二乘类辨识方法、极大似然法和预报误差法、时间序列模型和随机逼近法、多输入多输出性系统辨识、闭环系统辨识。附录给出了学习本课程中用到的矩阵分析等一些数学工具。 -Optimal state estimation and system identification Publisher: Northwestern University Press Author: Wang Zhixian This book describes the basic concepts and optimal state identification system, the basic theory and method of estimation. The book consists of two 14 chapters: The first chapter is the optimal state estimation, introduced the basic concepts of optimal estimation, Kalman filter for linear systems, optimal linear smoothing, divergence stability Kalman filter, and the filter which overcomes method, nonlinear filtering. The second is identification, introduced the general concept of system identification, impulse response and correlation function method, class identification method of least squares, maximum likelihood method and prediction error method, time series models and stochastic approximation method, and more input multi-output system identification, the closed-loop system identification. The appendix gives matrix analysis used in this course and some other mathematical
Platform: | Size: 6449152 | Author: 李赛 | Hits:

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