data are often used interchangeably, they are actually very different. Data is a set of unrelated information, and as such is of no use until it is properly evaluated. Upon evaluation, once there is some significant relation between data, and they show some relevance, then they are converted into information. Now this same data can be used for different purposes. Thus, till the data convey some information, t
HIGH SPeed serdes designs and connectors and simulation models simulations used in signal Integrity and also has practical evaluation aof all connectors
Description
The STM3210E-EVAL evaluation board is a
complete development platform for
STMicroelectronic's ARM Cortex-M3 core-based
STM32F103ZET6 or STM32F103ZGT6
microcontroller. The range of hardware features
on the board help you to evaluate all peripherals
(LCD, SPI Flash, USART, IrDA, USB, audio, CAN
bus, smartcard, MicroSD Card, NOR Flash,
NAND Flash, SRAM, temperature sensor, audio
DAC and motor control) and develop your own
applications.
Indian urbanization is a complex puzzle which is extremely difficult to comprehend.
Yet, as academicians, it is our responsibility to study, comprehend, analyse, assimi-
late, and express on salient happenings in our urban systems. The expressions aim
at the larger sections of the society to disseminate technical evaluation in a compre-
hensible note. This edition focuses on awaking the society on the contextual reality
of urban India and also enabling policymakers with the situational understanding of
Indian cities.
When joining Siemens in 2001, I also extended my research interest towards radio net-
work planning methodologies. This area of research brought together my personal interest
in mobile communications and in the design of efficient algorithms and data structures.
Between 2001 and 2003, I participated in the EU project Momentum, which was target-
ing the performance evaluation and optimization of UMTS radio networks. I
In general there are three different techniques for performance evaluation of
systems and networks: mathematical analysis, measurements, and computer
simulation. All these techniques have their strength and weaknesses. In the
literature there are plenty of discussions about when to use which technique,
how to apply it, and which pitfalls are related to which evaluation technique.
Performance analysis belongs to the domain of applied mathematics. The
major domain of application in this book concerns telecommunications sys-
tems and networks. We will mainly use stochastic analysis and probability
theory to address problems in the performance evaluation of telecommuni-
cations systems and networks. The first chapter will provide a motivation
and a statement of several problems.
This paper presents a Hidden Markov Model (HMM)-based speech
enhancement method, aiming at reducing non-stationary noise from speech
signals. The system is based on the assumption that the speech and the noise
are additive and uncorrelated. Cepstral features are used to extract statistical
information from both the speech and the noise. A-priori statistical
information is collected from long training sequences into ergodic hidden
Markov models. Given the ergodic models for the speech and the noise, a
compensated speech-noise model is created by means of parallel model
combination, using a log-normal approximation. During the compensation, the
mean of every mixture in the speech and noise model is stored. The stored
means are then used in the enhancement process to create the most likely
speech and noise power spectral distributions using the forward algorithm
combined with mixture probability. The distributions are used to generate a
Wiener filter for every observation. The paper includes a performance
evaluation of the speech enhancer for stationary as well as non-stationary
noise environment.
