FaultTolerantSystems
ME (VLSI & ESD)
(2013 course)
Module-1
Prof. Rashmi P.
Mahajan
Course Outcome
Students will able to understand the
modeling levels of the circuit and
types of simulation with module one.
Second module covers the fault
modeling and sim
VHDL AMS
36th Design Automation Conference New Orleans, June 21-25, 1999
Analog and Mixed-Signal Modeling Using the VHDL-AMS Language
Ernst Christen Beaverton, OR Kenneth Bakalar Rockville, MD Allen M. Dewey Durham, NC Eduard Moser Stuttgart, Germany
@8uv
EMBEDDED SYSTEMS
Course Content:
Module I: Introduction to an embedded systems design & RTOS:
Introduction to Embedded system, Processor in the System, Microcontroller, Memory Devices, Embedded
System Project Management, ESD and Co-design issues in System
Chapter 8: Network Security
Chapter goals: understand principles of network security:
cryptography and its many uses beyond confidentiality authentication message integrity key distribution
security in practice:
firewalls security in application, transpor
Chapter 6: Wireless and Mobile Networks
Background:
# wireless (mobile) phone subscribers now exceeds # wired phone subscribers! computer nets: laptops, palmtops, PDAs, Internet-enabled phone promise anytime untethered Internet access two important (but d
Chapter 2: Application layer
2.1 Principles of network applications 2.2 Web and HTTP 2.3 FTP 2.4 Electronic Mail
SMTP, POP3, IMAP
2.5 DNS
2.6 P2P file sharing 2.7 Socket programming with TCP 2.8 Socket programming with UDP 2.9 Building a Web server
2: App
Chapter 3: Transport Layer
Our goals: understand principles behind transport layer services:
multiplexing/demultipl exing reliable data transfer flow control congestion control
learn about transport layer protocols in the Internet:
UDP: connectionless tra
CHAPTER
13
Continuous Signal Processing
Continuous signal processing is a parallel field to DSP, and most of the techniques are nearly
identical. For example, both DSP and continuous signal processing are based on linearity,
decomposition, convolution and
CHAPTER
11
Fourier Transform Pairs
For every time domain waveform there is a corresponding frequency domain waveform, and vice versa. For example, a rectangular pulse in the time domain coincides with a sinc function [i.e., sin(x)/x] in the frequency doma
CHAPTER
10
Fourier Transform Properties
The time and frequency domains are alternative ways of representing signals. The Fourier transform is the mathematical relationship between these two representations. If a signal is modified in one domain, it will a
CHAPTER
12
The Fast Fourier Transform
There are several ways to calculate the Discrete Fourier Transform (DFT), such as solving
simultaneous linear equations or the c orrelation method described in Chapter 8. The Fast
Fourier Transform (FFT) is another me
CHAPTER
8
The Discrete Fourier Transform
Fourier analysis is a family of mathematical techniques, all based on decomposing signals into
sinusoids. The discrete Fourier transform (DFT) is the family member used with d igitized
signals. This is the first of
CHAPTER
9
Applications of the DFT
The Discrete Fourier Transform (DFT) is one of the most important tools in Digital Signal
Processing. This chapter discusses three common ways it is used. First, the DFT can calculate
a signal's frequency spectrum. This i
CHAPTER
2
Statistics, Probability and Noise
Statistics and probability are used in Digital Signal Processing to characterize signals and the processes that generate them. For example, a primary use of DSP is to reduce interference, noise, and other undesi
CHAPTER
3
ADC and DAC
Most of the signals directly encountered in science and engineering are continuous: light intensity
that changes with distance; voltage that varies over time; a chemical reaction rate that depends
on temperature, etc. Analog-to-Digit
CHAPTER
7
Properties of Convolution
A linear system's characteristics are completely specified by the system's impulse response, as governed by the mathematics of convolution. This is the basis of many signal processing techniques. For example: Digital fi
CHAPTER
6
Convolution
Convolution is a mathematical way of combining two signals to form a third signal. It is the single most important technique in Digital Signal Processing. Using the strategy of impulse decomposition, systems are described by a signal
CHAPTER
5
Linear Systems
Most DSP techniques are based on a divide-and-conquer strategy called superposition. The signal being processed is broken into simple components, each component is processed individually, and the results reunited. This approach ha
CHAPTER
DSP Software
4
DSP applications are usually programmed in the same languages as other science and engineering
tasks, such as: C, BASIC and assembly. The power and versatility of C makes it the language
of choice for computer scientists and other p
CHAPTER
1
The Breadth and Depth of DSP
Digital Signal Processing is one of the most powerful technologies that will shape science and
engineering in the twenty-first century. Revolutionary changes have already been made in a b road
range of fields: commun