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Daniel Sachs
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Adaptive Filtering: LMS Algorithm
(m10481)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Dima Moussa
,
Daniel Sachs
Keywords:
adaptive filtering
,
DSP
,
gradient descent
,
LMS
,
system identification
Summary:
This module introduces adaptive filters through the example of system identification using the LMS algorithm. The adaptive filter adjusts its coefficients to minimize the meansquare error between its output and that of an unknown system.
Subject:
Science and Technology
Language:
English
Popularity:
99.46%
Revised:
20090601
Revisions:
15
Using the Serial Port with a MATLAB GUI
(m12062)
Authors:
Jason Laska
,
Matthew Berry
,
Daniel Sachs
Keywords:
DSP
,
GUI
,
Matlab
,
Serial Port
Summary:
Explains how to send and receive data with the DSP through the serial port. Example code is shown in both assembly and C (for the DSP) as well as MATLAB for interfacing on the PC. Some example code for creating a MATLAB GUI is also shown.
Subject:
Science and Technology
Language:
English
Popularity:
99.42%
Revised:
20040625
Revisions:
New
Spectrum Analyzer: MATLAB Exercise
(m12379)
Authors:
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Jake Janovetz
,
Michael Kramer
,
Dima Moussa
,
Daniel Sachs
,
Brian Wade
,
Matt Kleffner
,
Douglas L. Jones
Keywords:
autocorrelation
,
bitreversed
,
boxcar
,
DFT
,
Discrete Fourier Transform
,
Discrete Time Fourier Transform
,
DSP
,
DTFT
,
Fast Fourier transform
,
FFT
,
Fourier transform
,
hamming
,
mainlobe
,
Power Spectra
,
Power Spectral Density Estimate
,
PSD
,
sidelobe
,
twiddlefactor
,
windowing
,
zeropad
Summary:
You will investigate the effects of windowing and zeropadding on the Discrete Fourier Transform of a signal, as well as the effects of dataset quantities and weighting windows used in Power Spectral Density estimation.
Subject:
Science and Technology
Language:
English
Popularity:
98.82%
Revised:
20040923
Revisions:
2
IIR Filtering: FilterDesign Exercise in MATLAB
(m10623)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Jake Janovetz
,
Michael Kramer
,
Dima Moussa
,
Daniel Sachs
,
Brian Wade
Keywords:
conv
,
difference equation
,
direct fortm II
,
DSP
,
ellip
,
elliptic lowpass filter
,
freqz
,
gain factor
,
IIR
,
impulse response
,
infinite impulse response
,
linear timeinvariant
,
LTI
,
notch filter
,
overflow
,
poles
,
zeros
Summary:
You will derive the transfer function of a secondorder, Direct Form II, infinite impulse response (IIR) filter. Then you will create a fourthorder IIR filter, plot its frequency response, and decompose the fourthorder filter into two secondorder sections, choosing an appropriate gain for each stage to prevent overflow.
Subject:
Science and Technology
Language:
English
Popularity:
98.76%
Revised:
20040225
Revisions:
12
Speech Processing: Theory of LPC Analysis and Synthesis
(m10482)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Jake Janovetz
,
Michael Kramer
,
Dima Moussa
,
Daniel Sachs
,
Brian Wade
Keywords:
autocorrelation
,
autocovariance
,
correlation
,
crosscorrelation
,
DSP
,
levinsondurbin
,
linear predicitive coding
,
speech
,
speech coding
,
speech compression
,
speech synthesis
Summary:
Speech analysis and synthesis with Linear Predictive Coding (LPC) exploit the predictable nature of speech signals. Crosscorrelation, autocorrelation, and autocovariance provide the mathematical tools to determine this predictability. If we know the autocorrelation of the speech sequence, we can use the LevinsonDurbin algorithm to find an efficient solution ... the speech.
[Expand Summary]
Speech analysis and synthesis with Linear Predictive Coding (LPC) exploit the predictable nature of speech signals. Crosscorrelation, autocorrelation, and autocovariance provide the mathematical tools to determine this predictability. If we know the autocorrelation of the speech sequence, we can use the LevinsonDurbin algorithm to find an efficient solution to the least meansquare modeling problem and use the solution to compress or resynthesize the speech.
[Collapse Summary]
Subject:
Science and Technology
Language:
English
Popularity:
98.59%
Revised:
20090601
Revisions:
20
Digital Transmitter: Introduction to Quadrature PhaseShift Keying
(m10042)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Jake Janovetz
,
Michael Kramer
,
Dima Moussa
,
Daniel Sachs
,
Brian Wade
Keywords:
DSP
,
gray coding
,
inphase signal
,
pseudonoise generator
,
QPSK
,
quadrature phaseshift keying
,
quadrature signal
,
signal constellation
Summary:
Quadrature phase shift keying (QPSK) is a method for transmitting digital data across an analog channel. Data bits are grouped into pairs and represented by a unique waveform, called a symbol. Data may be simulated with a pseudonoise sequence generator.
Subject:
Science and Technology
Language:
English
Popularity:
98.24%
Revised:
20040225
Revisions:
20
Two's Complement and Fractional Arithmetic for 16bit Processors
(m10808)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Dima Moussa
,
Daniel Sachs
,
Jason Laska
Keywords:
DSP
,
fractional arithmetic
,
overflow
,
two's complement
Summary:
Two'scomplement notation is a mathematically convenient way of representing signed numbers in microprocessors. The most significant bit of a two's complement number represents its sign, and the remaining bits represent its magnitude. Fractional arithmetic allows one to multiply numbers on an integer processor without incurring overflow. Fractional ... one bit.
[Expand Summary]
Two'scomplement notation is a mathematically convenient way of representing signed numbers in microprocessors. The most significant bit of a two's complement number represents its sign, and the remaining bits represent its magnitude. Fractional arithmetic allows one to multiply numbers on an integer processor without incurring overflow. Fractional arithmetic requires signextension of multipliers and multiplicands, and it requires the product of two numbers to be leftshifted one bit.
[Collapse Summary]
Subject:
Science and Technology
Language:
English
Popularity:
97.95%
Revised:
20050130
Revisions:
10
Digital Receivers: SymbolTiming Recovery for QPSK
(m10485)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Jake Janovetz
,
Michael Kramer
,
Dima Moussa
,
Daniel Sachs
,
Brian Wade
Keywords:
delaylocked loop
,
DSP
,
matched filter
,
noise
,
quadrature phaseshift keying
,
receiver
Summary:
The goal of symboltiming recovery is to sample message signals at the receiver for best performance. After the inphase and quadrature signals pass through a matched filter, a delaylocked loop attempts to find the peaks in the output waveforms.
Subject:
Science and Technology
Language:
English
Popularity:
97.94%
Revised:
20050729
Revisions:
15
Digital Receiver: Carrier Recovery
(m10478)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Dima Moussa
,
Daniel Sachs
Keywords:
BPSK
,
carrier recovery
,
coherent demodulation
,
digital communications
,
DSP
,
interpolation
,
numericallycontrolled oscillator
,
phaselocked loop
,
QPSK
,
voltagecontrolled oscillator
Summary:
The phaselocked loop (PLL) is a critical component in coherent communications receivers that is responsible for locking on to the carrier of a received modulated signal. A PLL adjusts the phase of a numericallycontrolled oscillator to match that of the received signal. You will simulate a carrier recovery ... the DSP.
[Expand Summary]
The phaselocked loop (PLL) is a critical component in coherent communications receivers that is responsible for locking on to the carrier of a received modulated signal. A PLL adjusts the phase of a numericallycontrolled oscillator to match that of the received signal. You will simulate a carrier recovery subsystem in MATLAB and then implement the subsystem on the DSP.
[Collapse Summary]
Subject:
Science and Technology
Language:
English
Popularity:
97.68%
Revised:
20090603
Revisions:
17
Speech Processing: LPC Exercise in MATLAB
(m10824)
Authors:
Douglas L. Jones
,
Swaroop Appadwedula
,
Matthew Berry
,
Mark Haun
,
Jake Janovetz
,
Michael Kramer
,
Dima Moussa
,
Daniel Sachs
,
Brian Wade
Keywords:
autocorrelation
,
DSP
,
levinsondurbin algorithm
,
linear predictive coding
,
speech
,
speech analysis
,
speech coding
,
speech compression
,
speech synthesis
,
xcorr
Summary:
You will write MATLAB code to compute the autocorrelation sequence of a simple signal. Then you will implement the LevinsonDurbin algorithm in MATLAB and analyze a recording of your own voice.
Subject:
Science and Technology
Language:
English
Popularity:
97.47%
Revised:
20040225
Revisions:
6
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