The concept of sustainable development has received growing recognition, but it is a new
idea for many business executives. For most, the concept remains abstract and
theoretical.
Protecting an organization’s capital base is a well-accepted business principle. Yet
organizations do not generally recognize
The concept of sustainable development has received growing recognition, but it is a new
idea for many business executives. For most, the concept remains abstract and
theoretical.
Protecting an organization’s capital base is a well-accepted business principle. Yet
organizations do not generally recognize
Hidden_Markov_model_for_automatic_speech_recognition
This code implements in C++ a basic left-right hidden Markov model
and corresponding Baum-Welch (ML) training algorithm. It is meant as
an example of the HMM algorithms described by L.Rabiner (1) and
others. Serious students are directed to the sources listed below for
a theoretical description of the algorithm. KF Lee (2) offers an
especially good tutorial of how to build a speech recognition system
using hidden Markov models.
Obtain the CDF plots of PAPR from an OFDM BPSK transmission specified per IEEE 802.11a specification
Per the IEEE 802.11a specifications, we 52 have used subcarriers. Given so, the theoretical maximum expected PAPR is 52 (around 17dB). However, thanks to the scrambler, all the subcarriers in an OFDM symbol being equally modulated is unlikely.
Using a small script, the cumulative distribution of PAPR from each OFDM symbol, modulated by a random BPSK signal is obtained
GloptiPoly 3: moments, optimization and
semidefinite programming.
Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem of
Moments (GPM), an infinite-dimensional optimization problem which can be viewed as
an extension of the classical problem of moments [8]. From a theoretical viewpoint, the
GPM has developments and impact in various areas of mathematics such as algebra,
Fourier analysis, functional analysis, operator theory, probability and statistics, to cite
a few. In addition, and despite a rather simple and short formulation, the GPM has a
large number of important applications in various fields such as optimization, probability,
finance, control, signal processing, chemistry, cristallography, tomography, etc. For an
account of various methodologies as well as some of potential applications, the interested
reader is referred to [1, 2] and the nice collection of papers [5].
An optimal neuron evolution algorithm for the restoration
of linearly distorted images is presented in this paper. The proposed
algorithm is motivated by the symmetric positive-definite quadratic programming
structure inherent in restoration. theoretical analysis and experimental
results show that the algorithm not only significantly increases
the convergence rate of processing, hut also produces good restoration
results. In addition, the algorithm provides a genuine parallel processing
structure which ensures computationally feasible spatial domain image
restoration
PDTDFB toolbox
The filter bank is described in:
The Shiftable Complex Directional Pyramid—Part I: theoretical Aspects
The Shiftable Complex Directional Pyramid—Part II: Implementation and Applications
IEEE transaction on singnal processing, Oct. 2008
Other related papers and software are available at:
nttruong.googlepages.com
Acknowledgement: The code development is based on the matlab code of the contourlet toolbox and the steerable pyramid.
This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and
This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and
This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and
