A series of .c and .m files which allow one to perform univariate and bivariate wavelet analysis of discrete time series. Noother wavelet package is necessary -- everything is contained in this archive. The C-code computes the DWT and maximal overlap DWT. MATLAB routines are then used to compute such quantities as the wavelet variance, covariance, correlation, cross-covariance and cross-correlation. Approximate confidence intervals are available for all quantities except the cross-covariance and cross-correlation.
A set of commands is provided. For a description of this example, please see http://www.eurandom.tue.nl/whitcher/software/.
One-channel queuing system simulator (M/M/1)
* Arrival and service times are random and distributed exponetially.
*
* The simulator is time-slice-driven, i.e. the system model is being
* run at discrete time points, with constant increments deltaT.
* At each such time moment, program checks if a new item arrival or
* release has occurred during previus deltaT.
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.
documentation for optimal filtering toolbox for mathematical software
package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter
and unscented Kalman filter for discrete time state space models. Also included in the toolbox
are the Rauch-Tung-Striebel and Forward-Backward smoother counter-parts for each filter, which
can be used to smooth the previous state estimates, after obtaining new measurements. The usage
and function of each method are illustrated with five demonstrations problems.
1
documentation for optimal filtering toolbox for mathematical software
package Matlab. The methods in the toolbox include Kalman filter, extended Kalman filter
and unscented Kalman filter for discrete time state space models. Also included in the toolbox
are the Rauch-Tung-Striebel and Forward-Backward smoother counter-parts for each filter, which
can be used to smooth the previous state estimates, after obtaining new measurements. The usage
and function of each method are illustrated with five demonstrations problems.
1
P3.18. An analog signal xa(t) = sin (100πt) is sampled using the following sampling intervals. In
each case plot the spectrum of the resulting Discrete-time signal.
Ts= 0.1 ms, Ts= 1 ms, Ts = 0.01 Sec
Title : Implementation of quadrature modulation and demodulation
Design Object : By implementing quadrature modulation and demodulation of analog signals in digital signal processing, students will have better understanding of sampling and frequency analysis of Discrete-time signals.
Design Content : Make a MATLAB function which performs quadrature modulation and demodulation for a input signal with anti-aliasing filtering.
Before delving into the details of orthogonal frequency division multiplexing (OFDM), relevant
background material must be presented first. The purpose of this chapter is to provide the necessary
building blocks for the development of OFDM principles. Included in this chapter are reviews of stochastic
and random process, Discrete-time signals and systems, and the Discrete Fourier Transform (DFT). Tooled
with the necessary mathematical foundation, we proceed with an overview of digital communication
systems and OFDM communication systems. We conclude the chapter with summaries of the OFDM
wireless LAN standards currently in existence and a high-level comparison of single carrier systems versus
OFDM.
