The
Iby and Aladar Fleischman


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Courses I teach
/ taught:
Discretetime Random Processes; Widesense stationary (WSS) processes and their properties; Linear parametric processes: AutoRegressive (AR), Moving Average (MA), ARMA; Spectral estimation: nonparametric methods (periodogram, correlogram, BlackmanTukey, Welch), parametric methods, YuleWalker (YW) and Modified YW equations; Detection of deterministic signals in noise: matched filter; Optimal linear filtering: causal and noncausal Wiener filters, Kalman filter; Introduction to adaptive filtering. Communication Systems Basic
concepts of communication systems, frequencydomain analysis of
deterministic signals vs. stochastic processes; Digital communication:
PulseAmplitude Modulation (PAM) and PulseCoding Modulation (PCM),
quantization and quantizationnoise; Matched Filter; InterSymbol
Interference (ISI) and eyepatterns; Line Codes; Delta Modulation;
Analog communication: Baseband signals, Noise Figure, Narrowband Noise
Characterization; Amplitudemodulation methods: DoubleSideBand (DSB),
Amplitude Modulation (AM), Single SideBand (SSB), Hilbert Transform and
its use; Phasemodulation methods: Phase Modulation (PM), Frequency
Modulation (FM), NarrowBand FM (NBFM); PhaseLocked Loops (PLL). Digital
Signal Processing Design of Finite Impulse
Response
(FIR) discretetime filters: Generalized Linear Phase (GLP) filters and
their
four types; Coefficients design methods: Impulseresponse Truncation
(IRT),
windowing, “optimal” windows, Leastsquares (LS) weighting approaches,
the
Alternation Theorem and related algorithms (ParksMcClellan, Remez
Exchange).
Implementation approaches, computational efficiency and finite
wordlength
considerations. Multirate signal processing, sampling rate conversion,
Polyphase filters, Multistage filtering, Filter banks, Quadrature
Mirror
Filters (QMF), conditions for perfect reconstruction. Concepts in
Linear
TimeVarying (LTV) systems: Tellegen’s theorem; generalization of
filterbanks
to timefrequency analysis, introduction to Wavelets. Digital
Processing of Single And MultiDimensional Signals SingleDimensional
signals:
Digital filtering principles, phase and amplitude relations, minimum
phase,
linear phase, group delay vs. phase delay, Generalized Linear Phase
(GLP)
filters; MultiDimensional (MD) signals and systems: MD Fourier
transform, MD
Ztransform, MD extensions of the Region of Convergence (ROC) concept,
stability issues; FIR coefficients design: Singledimensional: Impulse
Response
Truncation (IRT), windowing, LeastSquares approaches, ParksMcClellan
and
Remez exchange algorithms; MultiDimensional: zerophase filters, MD
windowing,
frequency sampling, transformation approaches, extensions of
singledimensional
tools; Mutirate processing of singledimensional signals, Polyphase
filters,
filter banks, perfect reconstruction, generalization of filterbanks to
timefrequency analysis, the relation to wavelets; Wavelets in MD
signal
processing, pyramid representations; Interpolation with splines. Advanced
Digital Signal Processing Lab The lab is based on TI’s
TMS320UC6416, and features five DSP experiments aimed at demonstrating
and
exploring both theoretical and practical considerations in realtime
implementation of DSP algorithms. The experiments include basic
introductory
functions, as well as more elaborate tasks such as realtime spectral
analysis,
FIR and IIR filtering and adaptive notch filtering. Introduction
to Signal Processing Discrete and continuous
signals and systems, classification, transformations, representation of
signals
in terms of an orthonormal basis; Linear, timeinvariant (LTI) systems,
impulse
response, convolution, exponential signals as eigensignals of LTI
systems;
Analysis of continuoustime periodic signals in terms of Fourier
series,
"continuousdiscrete" signals and discrete signals, analysis of
discretetime periodic signals using a discretetime Fourier series;
Analysis
of nonperiodic continuoustime and discretetime signals; The sampling
theorem, reconstruction of continuous signals; Unilateral and bilateral
Ztransform, its relation of the DiscreteTime Fourier Transform,
rational LTI
systems and their representation using difference equations. 