Description: this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.-this demo is to show you how to implement a ge neric SIR (a.k.a. particle, the bootstrap. Monte Carlo) filter to estimate the hidden stat es of a nonlinear. non-Gaussian state space model. Platform: |
Size: 6144 |
Author:大辉 |
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Description: To estimate the input-output mapping with inputs x
％ and outputs y generated by the following nonlinear,
％ nonstationary state space model:
％ x(t+1) = 0.5x(t) + [25x(t)]/[(1+x(t))^(2)]
％ + 8cos(1.2t) + process noise
％ y(t) = x(t)^(2) / 20 + 6 squareWave(0.05(t-1)) + 3
％ + time varying measurement noise
％ using a multi-layer perceptron (MLP) and both the EKF and
％ the hybrid importance-samping resampling (SIR) algorithm. -To estimate the input-output mapping with inputs x and outputs y generated by the following nonlinear, nonstationary state space model: x (t+ 1) = 0.5x (t)+ [25x (t )]/[( 1+ x (t)) ^ (2)]+ 8cos (1.2t)+ process noise y (t) = x (t) ^ (2)/20+ 6 squareWave (0.05 (t-1 ))+ 3+ time varying measurement noise using a multi-layer perceptron (MLP) and both the EKF and the hybrid importance-samping resampling (SIR) algorithm. Platform: |
Size: 40960 |
Author:Lin |
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Description: In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The optimal quantizer stepsize which maximizes the MMSE receiver output SNR is also determined.-In this project we analyze and design the minimum mean-square error (MMSE) multiuser receiver for uniformly quantized synchronous code division multiple access (CDMA) signals in additive white Gaussian noise (AWGN) channels.This project is mainly based on the representation of uniform quantizer by gain plus additive noise model. Based on this model, we derive the weight vector and the output signal-to-interference ratio (SIR) of the MMSE receiver. The effects of quantization on the MMSE receiver performance is characterized in a single parameter named 鈥漞quivalent noise variance鈥? The optimal quantizer stepsize which maximizes the MMSE receiver output SNR is also determined. Platform: |
Size: 147456 |
Author:prasad |
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Description: 这是SIR微分方程模型对初值问题的求解和作图-This is the SIR model differential equations to solve the problem of initial value and mapping Platform: |
Size: 1024 |
Author:kreaya |
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Description: 这个一个完好无损的matlab程序，他实现的功能是进行扩展开尔曼滤波，是本人亲自制造的，哈哈，哈哈哈，-this demo is to show you how to implement a generic SIR (a.k.a. particle, bootstrap, Monte Carlo) filter to estimate the hidden states of a nonlinear, non-Gaussian state space model.-this demo is to show you how to implement a ge neric SIR (a.k.a. particle, the bootstrap. Monte Carlo) filter to estimate the hidden stat es of a nonlinear. non-Gaussian state space model. Platform: |
Size: 1024 |
Author:tian |
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Description: 复杂网络的MATLAB仿真，有AB和BA模型，WS和NW小世界模型，并对他们的统计特征进行分析比较-MATLAB simulation of complex networks, with AB and BA model, WS and NW small-world model, and their statistical analysis and comparison of features Platform: |
Size: 10240 |
Author:汤健 |
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Description: SIR模型是传染病模型中最经典的模型，其中S表示易感者，I表示感染者，R表示恢复者。SIR模型中，染病人群为传染的源头,他通过一定的几率把传染病传给易感人群,他自己也有一定的几率/可以被治愈并免疫,或者死亡;易感人群一旦被感染,就又成为了新的传染源。将人群划分为三类，易感染者、已感染者和已恢复者(recovered )。(The SIR model is the most classic model in the infectious disease model, where S represents a susceptible person, I represents an infected person, and R represents a recovering person. In the SIR model, the infected patient group is the source of infection. He transmits the infectious disease to the susceptible population through a certain probability. He also has a certain chance/can be cured and immunized, or died; once the susceptible population is infected, it is again Become a new source of infection. The population is divided into three categories, susceptible to infection, infected and recovered.) Platform: |
Size: 1024 |
Author:小马mx |
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Description: 元胞自动机(cellular automata, CA)是时间和空间都离散的动力学系统。时至今日，已经广泛应用于社会、经济、军事和科学研究等各个领域。本程序是基于元胞自动机的原理，利用matlab编程，复现了二维状态下“生命游戏”的原型，森林树，以及SIR传染病模型，以帮助正在入门学习元胞自动机的人们加深其原理的理解。(Cellular automata (CA) is a dynamic system with discrete time and space. Today, it has been widely used in social, economic, military and scientific research and other fields. This program is based on the principle of cellular automata, using MATLAB programming, reproduce the two-dimensional state of "life game" prototype, forest tree, and SIR epidemic model, in order to help people who are learning cellular automata to deepen their understanding of its principle) Platform: |
Size: 3072 |
Author:zjzjzzz |
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