...A310SE ADVANCED DIGITAL SYSTEM
TABLE OF CONTENTS
1. Abstract………………………………………………………………………….....2
1.1. What is low pass IIR filter………………… ……………………….….....3
2. Introduction……………………………………………………………………......5
3. Main Report ………………………………………………………………………7
3.1 Principle of specification of IIR digitalfilter……………………………7
3.2 Principle of Low Pass filter………………………………….......……..…8
3.3 Characteristic of classical analog filter…...............................................10
3.4 Digitalfilter design steps by BZT method………………………………15
3.5 Functional Architecture of TMS320C6713……………………………16
4. Design Criteria……………………………………………………………………15
4.1 Design calculation for IIR FTR filter by BZT method…………….….17
4.2Flow chart for matlab program……………………………….................21
4.3 Flow chart for CSC program………………………………………..…22
5. Software Implementation………………………………………………….………24
5.1 Matlab programme for filter coefficient ……………………………..….24
5.2 CSC program for interfacing and implementation of digitalfilter............27
5.3 Simulation results………………………………………………………….28
6. Implementaton of digitalfilter on TMSC6713 DSP chip……………………….....29
6.1 Detail implementation steps and procedure………..………...…..……29
6.2 Emulation result………………………………………………………...42
7. Critical analysis...

...Lab manual for
Digital Signal Processing Lab
III B. Tech II Semester
Prepared by
J. Sunil Kumar, P.Saritha & Ch.Sateesh kumar reddy
Department of Electronics & Communication Engineering
Turbomachinery Institute of Technology & Sciences
(Approved by AICTE & Affiliated to JNTUH) Indresam(v), Patancheru(M), Medak(Dist). Pin: 502 319
Date:…………
DSP Lab Manual ………
Turbomachinery Institute of Technology & Sciences
Certificate
This is to certify that Mr. / Ms. ………………………………….. RollNo……………..… of I/II/III/IV B.Tech I / II Semester of …………….……………………..…………branch has completed the laboratory work satisfactorily in …………………..…….……..... Lab for the academic year 20 … to 20 …as prescribed in the curriculum. Place: …………….….
Date: ……………..….
Lab In charge
Head of the Department
Principal
.
1
Turbomachinery Institute of Technology & Sciences, Hyd. 319
Date:………… LIST OF EXPERIMENTS: 1. Generation of Sinusoidal Waveform / Signal 2. To find the DFT / IDFT of given DT Signal
DSP Lab Manual ………
3. To find the frequency response of a given system in transfer function 4. Implementation of FFT of given sequence 5. Implementation of LP FIR filter for given sequence 6. Implementation of HP FIR filter for given sequence 7. Implementation of LP IIR filter for given sequence 8. Implementation of HP IIR filter for given sequence 9. Determination of power spectrum of a given...

...about the adaptive filter coefficients after a large number of iterations [3].
This thesis consists of designing and implementing an echo canceling system. The DSP chip is used to simulate the echo creating system and to implement the adaptive filtering system to cancel the echo in the distorted signal. Initially, the adaptive filter coefficients are far from the ideal numbers. After several iterations, the LMS algorithm will update these coefficients to converge on an optimal set of coefficients. Simulations of the LMS algorithm will be done in MATLAB to get approximate performance specifications before implementation.
MSE plots that are called learning curves in the DSP field will be attained. The learning curves as well as the magnitude of the frequency response of the adaptive filter coefficients will be used to determine the performance of our system. Convergence of the adaptive filter coefficients and the similarity of the coefficient values in simulation and experimentation will also be of vital significance.
The Least Mean Square (LMS) algorithm is a well-known adaptive estimation and prediction technique [4]. It has been extensively studied in the literature and widely used in a variety of applications. The performance of the LMS algorithm is highly dependent on the selected convergence parameter μ and the signal condition. A larger convergence parameter value leads to faster convergence of the LMS...

...I. Introduction
A. Definition of the Filter
The raised cosine filter is a finite impulse response filter (FIR) which is commonly used for pulse shaping in digital modulation minimize interference . The interference is controlled in a manner that it exists only at some samples other than the samples of the original signal. Its name stems from the fact that the non-zero portion of the frequency spectrum of its simplest form is a cosine function, raised - up to sit above the frequency axis.
B. Brief Background of the Filter
Data, in communication systems, are transmitted in binary form – a combination of ones and zeroes. Most implementations of a binary system is with the use of switches. When the switch is turned on, it means logic ‘1’ and off for logic ‘0’. These ones and zeroes may represent a rectangular pulse. In the frequency domain of this rectangular pulse, an infinite duration sinc pulse can be manifested.
Figure 1. A Rectangular Pulse Train Figure 2. A Sinc Function
Taking a single rectangular pulse from the pulse train in Figure 1, it can be noted that the energy is concentrated within the limit of half the time interval. This event implies to sum the halves so that it may equal to one pulse duration, which in concept, may require twice the bandwidth for a reliable transmission. Hence, a limitation is imposed upon when considering a bandwidth limited system, if the...

...VLSI IMPLEMENTATION OF ARRAY BASED FIR FILTER FOLDING
A PROJECT REPORT
Submitted by POORNIMA.K (41502106067) REKHA.H (41502106084) SARADA VINAYAK (41502106090)
in partial fulfillment for the award of the degree of BACHELOR OF ENGINEERING in ELECTRONICS AND COMMUNICATION ENGINEERING
SRM ENGINEERING COLLEGE, KATTANKULATHUR ANNA UNIVERSITY:: CHENNAI 600 025 APRIL 2006
ANNA UNIVERSITY : CHENNAI 600 025
BONAFIDE CERTIFICATE
Certified that this project report “VLSI IMPLEMENTATION OF ARRAY BASED FIR FILTER FOLDING” is the bonafide work of POORNIMA.K (41502106067), REKHA.H (41502106084) SARADA VINAYAK (41502106090) who carried out the project work under my supervision.
SIGNATURE DR.S.JAYASHRI HEAD OF THE DEPARTMENT
SIGNATURE MR.J.SELVAKUMAR SUPERVISOR LECTURER
ELECTRONICS AND COMMUNICATION ENGG. SRM Engineering College SRM nagar Kattankulathur Kancheepuram 603203
ELECTRONICS AND COMMUNICATION ENGG. S.R.M Engineering College SRM nagar Kattankulathur Kancheepuram 603203
INTERNAL EXAMINER ACKNOWLEDGMENT
EXTERNAL EXAMINER
We express our sincere thanks to the Chairman, Thiru.T.R.Pachamuthu, the Director, Mr.T.P.Ganesan, and the management. We are grateful to our Principal, Prof.K.Venkataramani for his support and direction in the course of the project.
We take great pleasure in thanking our Head of the Department, Dr.S.Jayashri who has always been a source of inspiration. Her constant motivation has been a...

...The Hong Kong Polytechnic University Department of Electronic and Information Engineering EIE413 Digital Signal Processing Individual Essay
Multirate Digital Signal Processing
Instructor: W.C. Siu By HAN Shilu 07828567D
EIE413 Digital Signal Processing
Multirate Digital Signal Processing
Abstract
In traditional digital signal processing system, there is always only one simple sampling rate (that is, the sampling frequency). The output signal has the same sampling rate with the input. In modern digital systems, however, there is an
increasing need to process data at more than one sampling rate. Sometimes the output of the system is required to have a different sampling rate of the input signal. This has lead the development of multirate digital signal processing, which is a new sub-area in DSP. For example, the sampling rate for an audio CD (compact disc) is 44.1 kHz. If we want to transfer data from the CD to a DAT (digital audio tape) at a sampling rate of 48 kHz, we need to increase the frequency of the data first using a multirate approach. There are two primary options we have in multirate processing. The first is decimation. The sampling rate fs of a given signal x[n] is decreased. This approach is also called down sampling. The second is interpolation. We can increase the sampling rate fs of the given signal x[n]. This approach is also...

...Digital signal processing
Digital signal processing
Digital signal processing (DSP) is the mathematical manipulation of an information signal to modify or improve it
in some way. It is characterized by the representation of discrete time, discrete frequency, or other discrete domain
signals by a sequence of numbers or symbols and the processing of these signals.
The goal of DSP is usually to measure, filter and/or compress continuous real-world analog signals. The first step is
usually to convert the signal from an analog to a digital form, by sampling and then digitizing it using an
analog-to-digital converter (ADC), which turns the analog signal into a stream of numbers. However, often, the
required output signal is another analog output signal, which requires a digital-to-analog converter (DAC). Even if
this process is more complex than analog processing and has a discrete value range, the application of computational
power to digital signal processing allows for many advantages over analog processing in many applications, such as
error detection and correction in transmission as well as data compression.
Digital signal processing and analog signal processing are subfields of signal processing. DSP applications include:
audio and speech signal processing, sonar and radar signal processing, sensor array processing, spectral...