Carrier-phase synchronization can be approached in a general manner by estimating the multiplicative distortion (MD) to which a baseband received signal in an RF or coherent optical transmission system is subjected. This paper presents a unified modeling and estimation of the MD in finite-alphabet digital communication systems. A simple form of MD is the camer phase exp GO) which has to be estimated and compensated for in a coherent receiver. A more general case with fading must, however, allow for amplitude as well as phase variations of the MD. We assume a state-variable model for the MD and generally obtain a Nonlinear estimation problem with additional randomly-varying system parameters such as received signal power, frequency offset, and Doppler spread. An extended Kalman filter is then applied as a near-optimal solution to the adaptive MD and channel parameter estimation problem. Examples are given to show the use and some advantages of this scheme.
標簽： synchronization Carrier-phase multiplicativ approached
上傳時間： 2013-11-28
上傳用戶：windwolf2000
In this article, we present an overview of methods for sequential simulation from posterior distributions. These methods are of particular interest in Bayesian filtering for discrete time dynamic models that are typically Nonlinear and non-Gaussian. A general importance sampling framework is developed that unifies many of the methods which have been proposed over the last few decades in several different scientific disciplines. Novel extensions to the existing methods are also proposed.We showin particular how to incorporate local linearisation methods similar to those which have previously been employed in the deterministic filtering literature these lead to very effective importance distributions. Furthermore we describe a method which uses Rao-Blackwellisation in order to take advantage of the analytic structure present in some important classes of state-space models. In a final section we develop algorithms for prediction, smoothing and evaluation of the likelihood in dynamic models.
標簽： sequential simulation posterior overview
上傳時間： 2015-12-31
上傳用戶：225588
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.
標簽： input-output the generated following
上傳時間： 2014-01-05
上傳用戶：royzhangsz
Support Vector Machine is small sample method based on statistic learning theory. It is a new method to deal with the highly Nonlinear classification and regression problems .It can better deal with the small sample, Nonlinear and
標簽： method statistic learning Support
上傳時間： 2014-12-02
上傳用戶：zukfu
Traveling Salesman Problem (TSP) has been an interesting problem for a long time in classical optimization techniques which are based on linear and Nonlinear programming. TSP can be described as follows: Given a number of cities to visit and their distances from all other cities know, an optimal travel route has to be found so that each city is visited one and only once with the least possible distance traveled. This is a simple problem with handful of cities but becomes complicated as the number increases.
標簽： interesting Traveling classical Salesman
上傳時間： 2016-02-06
上傳用戶：rocwangdp
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
an analysis software with souce code for the time series with methods based on the theory of Nonlinear deterministic dynamical systems, or chaos theory.這套軟件源碼是根據H. Kantz and T. Schreiber, ``Nonlinear Time Series Analysis , Cambridge University Press, Cambridge (1997).
標簽： with the analysis software
上傳時間： 2013-12-10
上傳用戶：ve3344
GNU Octave is a high-level language, primarily intended for numerical computations. It provides a convenient command line interface for solving linear and Nonlinear problems numerically.
標簽： computations high-level primarily numerical
上傳時間： 2014-01-07
上傳用戶：星仔
小波神經網絡的源程序: 1.構造的非線性函數: 位于nninit_test.m 2.直接用WNN逼近非線性:Wnn_test.m, (內部調用小波函數) 3.遺傳算法優化后逼近 :GA_Wnn_test.m (內部調用遺傳算法的,初始化,適應度,解碼函數)-genetic algorithm optimization WNN source : 1. Construction of the Nonlinear function : nninit_test.m at 2. WNN directly with Nonlinear approximation : Wnn_test.m. (internal called wavelet function) 3. Genetic Algorithm optimization approach : GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions)
標簽： nninit_test GA_Wnn_tes Wnn_test WNN
上傳時間： 2016-09-17
上傳用戶：LIKE
非線性有限元程序，NONSAP is a general finite element program for the Nonlinear static and dynamic analysis of complex structures. The program is very flexible and was designed to be extended and modified by the user. In particular the program can easily be modified to use a different formulation of the equations of motions, different time integration operators and other additional options.
上傳時間： 2016-11-12
上傳用戶：hopy
