基于OFDM的無線寬帶系統仿真It contains mainly two parts, i.e. link-level simulator and system-level simulator. Link-level simulator focus on a single-cell single-user scenario, where signal is transmitted from tx, and estimated at rx. Comparing the difference in tx/rx signal, the error rate can be found out. The output of the link-level simulator is the BLER/BER vs. SNR mapping table, that can be used for the system-level Simulation. System-level simulator focus on a multi-cell multi-user scenario. For the sake of simplicity, it takes the mapping table aquired in the link-level Simulation, measure the actural SNR, and finds the corresponding error rate.
標簽： simulator i.e. system-level link-level
上傳時間： 2016-03-15
上傳用戶：xsnjzljj
Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assuming BPSK. Brute force Monte Carlo approach is unsatisfactory (takes too long) to find the BER curve. The computation uses a quasi-analytic (QA) technique that relies on the estimation (approximate one) of the information-bits Weight Enumerating Function (WEF) using A Simulation of the convolutional encoder. Once the WEF is estimated, the analytic formula for the BER is used.
標簽： convolutional Computes encoding decision
上傳時間： 2013-12-24
上傳用戶：咔樂塢
Testbenches have become an integral part of the design process, enabling you to verify that your HDL model is sufficiently tested before implementing your design and helping you automate the design verification process. It is essential, therefore, that you have confidence your testbench is thoroughly exercising your design. Collecting code coverage statistics during Simulation helps to ensure the quality and thoroughness of your tests.
標簽： Testbenches enabling integral process
上傳時間： 2016-03-24
上傳用戶：1109003457
Simple VaR Calculator provides: - Evaluation of return distribution of single asset or portfolio of assets - Volatility forecasts using moving average and exponential algorithm - Value at Risk of single asset or portfolio measurement using parametric and historical Simulation. - Historical data can be obtained from simple text file or MS Excel using Matlab Excel Links.
標簽： distribution Calculator Evaluation portfolio
上傳時間： 2013-12-21
上傳用戶：hasan2015
On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the Simulation progress (with par.doPlot=1) and modify the Simulation parameters.
標簽： demonstrates sequential Selection Bayesian
上傳時間： 2016-04-07
上傳用戶：lindor
D-S.Kim, Y.S.Lee, W.H.Kwon, and H.S.Park, "Maximum Allowable Delay Bounds in Networked Control Systems", Control Engineering Practice (Elsvier Science) (Simulation Example - Matlab Code), PP.1301-1313, Vol.11, Issue 11, December, 2003
標簽： Allowable Networked Control Maximum
上傳時間： 2016-04-10
上傳用戶：lifangyuan12
H.S.Park, D-S.Kim, and W.H.Kwon "A Scheduling Method for Network-based Control Systems", IEEE Transaction on Control System Technology, Vol.10, No.3, pp. 318-330, May, 2002 (Simulation Example 1- Matlab Code)
標簽： Network-based Scheduling Control Systems
上傳時間： 2014-01-20
上傳用戶：cainaifa
A new PLL topology and a new simplified linear model are presented. The new fractional-N synthesizer presents no reference spurs and lowers the overall phase noise, thanks to the presence of a SampleJHold block. With a new Simulation methodology it is possible to perform very accurate Simulations, whose results match closely those obtained with the linear PLL model developed.
標簽： new fractional-N synthesizer simplified
上傳時間： 2016-04-14
上傳用戶：hjshhyy
The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generic and suitable for any application. For details, please refer to Rao-Blackwellised Particle Filtering for Fault Diagnosis and On Sequential Simulation-Based Methods for Bayesian Filtering After downloading the file, type "tar -xf demo_rbpf_gauss.tar" to uncompress it. This creates the directory webalgorithm containing the required m files. Go to this directory, load matlab and run the demo.
標簽： filtering particle Blackwellised conditionall
上傳時間： 2014-12-05
上傳用戶：410805624
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and Simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the Simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
標簽： Rauch-Tung-Striebel algorithm smoother which
上傳時間： 2016-04-15
上傳用戶：zhenyushaw
