
- PS #3 , Spring 2001 Signal Processing Using MATLAB, EECE-495
- Example: Power Spectral Factorization Consider a zero-mean, second-order, WSS, random sequence x[n], whose power
- Problem Set # 5.0 EECE-495/595, Spring 2002
- Overview of FIR Wiener Filtering For the optimal FIR Wiener filter, the estimate of the signal of interest (SOI)
- Solution to PS #1 , Spring 2004 Digital Signal Processing, EECE-539
- PUBLICATIONS Journal Articles
- Problem Set # 3.0 EECE-495/595, Spring 2002
- MidTerm Make-up Exam, Fall 2003 EECE340, Probability and Statistics
- ECE595, Section 011, Fall 2011 Adaptive Filtering
- Total Probability and Bayes Theorem Consider a random experiment with sample space S. Let Bi, i = 1, . . . , n be
- Upsampling and Downsampling In the previous section we looked at upsampling and the downsampling as specific forms of sampling. In this
- Solutions to PS # 7.0 Problem Solving Using MATLAB
- ICASSP 2004, Montreal, Canada
- Problem Set #5.0 ECE-541, Fall 2010
- Examples: Polyphase Decomposition Consider a moving average system with system function of the form
- Overview of Causal Wiener Filtering For the optimal causal IIR filter, the estimate of the signal of interest(SOI)
- On Least Squares Inversion A problem of importance that we will see appear often in optimal estimation is
- Notes on Filterbanks In class, we have seen that the Nyquist sampling theorem specifies a minimum sampling rate for a band-
- MidTerm Exam II, Fall 2003 EECE340, Probability and Statistics
- IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 48, NO. 3, MARCH 2000 473 Multicomponent AMFM Demodulation via
- 294 IEEE SIGNAL PROCESSING LETTERS, VOL. 3, N0. 11, NOVEMBER 1996 Energy Demodulation of Two{Component AM{FM
- Quantization Noise Shaping Via Oversampling Now that we have a basic idea of the effect that a decimation system has on a
- ICA BASED BLIND ADAPTIVE MAI SUPPRESSION IN DS-CDMA SYSTEMS Malay Gupta and Balu Santhanam
- Solutions to Problem Set #1 EECE-595, Section II
- Multicomponent AM--FM Energy Demodulation with Applications to Signal
- Prior ICA Based Blind Multiuser Detection in DS-CDMA Systems
- Applications of Adaptive FilteringApplications of Adaptive Filtering Communication Systems : (a) channel equalization for
- On a SturmLiouville Framework for Continuous and Discrete Frequency Modulation
- Cascade of Decimation Systems In class, we looked at the decimation operation in detail and observed that it
- Geometric Probability Law Consider a sequential experiment Ai, i = 1, 2, . . . , n in which we repeat
- MidTerm Exam I, Fall 2003 EECE340, Probability and Statistics
- On Mean Squared Continuity In class, we have see the notion of convergence in the mean-squared sense of
- Order Statistics Let X1, X2 be independent random variables defined on a sample space S 2
- PS #3 , Spring 2011 Digital Signal Processing, ECE-539
- Solution to PS #3 , Spring 2011 Digital Signal Processing, ECE-539
- ECE314: Signals and Systems Fall 2009 Solution: Homework 4
- Sufficiency Of SecondOrder Statistics Consider a fourth-order Gaussian random vector X = [X1, X2, X3, X4]T
- Example: cyclostationary process Consider a random process X(t) that is defined via the relation
- ECE-541: Probability Theory & Stochastic Processes University of New Mexico, Albuquerque
- Problem Set #1 EECE-595, Section II
- INSTANTANEOUS ENERGY OPERATORS: APPLICATIONS TO SPEECH PROCESSING AND COMMUNICATIONS
- 2 Cyclostationarity In the determinitic case, a signal is called periodic if it repeats after a period of time. In
- On Mean Squared Convergence A concept that is central to the notion of metric spaces and also to any
- Minimum Phase and Allpass Systems Minimum Phase Systems
- Problem Set #2 ECE-541, Fall 2010
- Optimum Nonlinear Estimation Consider two random variables X() and Y () defined on the same sample
- Guidelines to MATLAB Project In regards to the maximum likelihood binary detector in AWGN
- DSP WKSHP 2002 ENERGY SEPARATION ANDENERGY SEPARATION AND
- Problem Set #2 EECE-595, Section II
- On Modes of Convergence of Random Sequences Consider again the notion of a probability space and the underlying triplet
- DKF: AssumptionsDKF: Assumptions Known state model for desired process
- Counting Rules Reading Assignment: Section 2.3
- Midterm Exam I, Fall 2008 Signals and Systems
- Filtering of Random Signals Consider a discrete-time LTI system with a system function of the form
- Solution to Problem Set # 2.0 ECE-595, Fall 2006
- AN IMPROVED SPECTROGRAM USING THE MULTIANGLE CENTERED DISCRETE FRACTIONAL FOURIER TRANSFORM
- Optimal Wiener Deconvolution The Wiener deconvolution problem seeks to extract an estimate of the SOI d[n] from observations of the
- LTI Systems and Random Signals Consider a LTI system with a transfer function H(s) which is excited with a WSS random signal X(t), with
- Curriculum Vitae Balu Santhanam
- PS #1 , Fall 2009 Signals and Systems, ECE-314
- University of New Mexico, Albuquerque Department of Electrical and Computer Engineering
- University of New Mexico, Albuquerque Department of Electrical and Computer Engineering
- Solution to Problem Set # 4.0 ECE-595, Fall 2006
- University of New Mexico, Albuquerque Department of Electrical and Computer Engineering
- Rayleigh and Rician Fading Consider two independent normal random variables X N(m1, 2) and
- Properties of the Covariance Matrix The covariance matrix of a random vector X Rn
- Binomial Probability Law Consider a sequence of independent events Xi, i = 1, 2, . . . , n that are binary
- Transmultiplexers as precoders in modern digital communication: a tutorial review P. P. Vaidyanathan and B. Vrcelj
- Spectral Zoom Operation In our previous discussion we have mentioned that the decimation operation corresponds to a spectral zoom
- Sequences with Rational Power Spectra Consider the class of zero-mean, finite variance, WSS, random sequences with
- Bivariate Gaussian random variable Let X be a bivariate gaussian random variable, i.e., X N(, ). Denote the
- Problem Set #5.0 ECE541, Fall 2005
- Expected Values and Averages Although the PDF, CDF, and the characteristic function of a random variable
- Adaptive Linear Predictive Frequency Tracking and CPM Demodulation
- PS #6 , Spring 2011 Digital Signal Processing, ECE-539
- Non Uniform Quantization Functions Optimal Output Alphabets and Levels
- DISCRETE GAUSS-HERMITE FUNCTIONS AND EIGENVECTORS OF THE CENTERED DISCRETE FOURIER TRANSFORM
- On a Pseudo-Subspace Framework for Discrete Fractional Fourier Transform Based Chirp
- THE CENTERED DISCRETE FRACTIONAL FOURIER TRANSFORM AND LINEAR CHIRP SIGNALS
- Power Spectral Factorization Consider a zero-mean, WSS, discrete-time, random signal with a power spec-
- On Mean Squared Derivatives Armed with the knowledge of mean-squared convergence of a sequence of ran-
- Frequency Response of FIR Linear Phase Systems FIR, linear phase systems fall into one of 4 categories
- Sequences with Rational Power Spectra Consider the class of zero-mean, finite variance, WSS, random sequence with
- On Statistical Regularity Before one proceeds to the notion of a probability measure defined on a sample
- Adaptive Linear Predictive FrequencyAdaptive Linear Predictive Frequency Tracking and CPM DemodulationTracking and CPM Demodulation
- Review-DSIP UNM MURI REVIEW 2002UNM MURI REVIEW 2002
- Signal Processing 69 (1998) 81--91 Harmonic analysis and restoration of separation methods for
- IEEE SIGNAL PROCESSING LETTERS, VOL. 11, NO. 3, MARCH 2004 341 Generalized Energy Demodulation for Large
- IEEE SIGNAL PROCESSING LETTERS, VOL. 12, NO. 4, APRIL 2005 273 On the Multiangle Centered Discrete Fractional
- This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research
- 402 IEEE SIGNAL PROCESSING LETTERS, VOL. 16, NO. 5, MAY 2009 A Hybrid ICA-SVM Approach to Continuous
- Proceedings of 1996 IEEE Int'l Conf. on Acoustics, Speech and Signal Processing, Atlanta, May 1996. 3517 ENERGY DEMODULATION OF TWO{COMPONENT AM{FM SIGNALS WITH
- Proceedings of 1997 Int'l Conf. on Acoustics, Speech & Signal Processing, Munich, Germany, April 1997. 2409 DEMODULATION OF DISCRETE MULTICOMPONENT AM{FM SIGNALS USING
- Funded Research 1 Resolution Enhancement for Optical Nanolithography
- Curriculum Vitae Balu Santhanam
- MATLAB PrimerThird Edition Kermit Sigmon
- PS #3 , Fall 2009 Signals and Systems, ECE-314
- PS #5.0 , Fall 2009 Signals and Systems, ECE-314
- Midterm Exam II, Fall 2008 Signals and Systems
- Random Processes: Notation and Definitions Consider the probability space, (, F, P), where we have seen that random
- 1 Stationarity A random signal X(t) is said to be strict sense stationary (SSS) if the nth
- 3 Ergodic Processes In the event that the distributions and statistics are not available we can avail ourselves of
- Ergodicity in the Mean A WSS random process is said to be ergodic in the mean if the time-average estimate of the mean obtained
- Statistical Model for White Noise A random signal X(t) is said to be a strictly white random signal if the the constituent random
- Hilbert Spaces and Random Vectors Consder the random vectors of dimension n defined on Rn
- Example: Oscillator with Random Phase Consider the output of a sinusoidal oscillator that has a random phase and amplitude of the
- Random Process: Example Outcome Sample function
- Modulation of Random Processes Let us now consider the modulation of a random process X(t) with the random-phase sinu-
- Transformation of Random Vectors: Continued White Random Vectors
- Random Signals & Multirate Systems Now that we have a basic understanding of the decimation and interpolation
- Overview of Optimal Wiener Filtering For the optimal Wiener filter, the estimate of the signal of interest (SOI) takes the form
- Least Squares : MotivationLeast Squares : Motivation SDA/LMS assume a probabilistic model underlying the
- Problem Set #1 ECE-541, Fall 2010
- Problem Set #3 ECE-541, Fall 2010
- Problem Set #4, MATLAB Assignment ECE-541, Fall 2010
- University of New Mexico, Albuquerque Department of Electrical and Computer Engineering
- Interpolation & Decimation This document is intended to be a guide for the various interpolation and deci-
- Polyphase Decomposition The multirate operations of decimation and interpolation that were introduced
- Non Uniform Quantization In class we looked at the additive noise model for uniform quantization, where
- PS #4.0 , Spring 2011 Digital Signal Processing, ECE-539
- University of New Mexico, Albuquerque Department of Electrical & Computer Engineering
- Problem Set # 2.0 ECE-595, Fall 2006
- PS # 4.0, Spring 2002 Engineering Problem Solving Using MATLAB
- Problem Set # 7.0 Signal Processing Exercises in MATLAB
- Solution to PS # 6.0, Spring 2002 Problem Solving Using MATLAB, EECE-495/595
- Problem Set # 7.0 EECE-495, Spring 2001
- University of New Mexico, Albuquerque Department of Electrical and Computer Engineering
- Definitions of Probability Reading Assignment: Sections 2.1, 2.2
- Random variables Let S denote the sample space underlying a random experiment with elements
- On the Toss of a Coin Consider the random experiment of tossing a fair coin. There are two possible
- Example on Characteristic Functions Consider a random variable X defined on a sample space S that is Gamma
- Generating a RV with a Specified CDF Let X be a continuous random variable defined over a sample space S with a specified CDF FX(x).
- Examples on Transformations of Random Variables 1. Let X U([-, ]). Find the distribution of the random variable Y =
- Independence and Uncorrelatedness On the surface these two statistical notions look identical, however, there is a
- Transformation of Random Vectors: Our goal in this section is to develop analytical results for the probability distribution function
- Problem Set # 4.0 EECE-340, Probability and Statistics
- MATLAB Project EECE-340, Fall 2003
- Problem Set #6 EECE-340, Fall 2003
- LMS Algorithm: MotivationLMS Algorithm: Motivation Only a single realization of observations available.
- Leaky LMS AlgorithmLeaky LMS Algorithm Convergence of tap-weight error modes dependent on
- RLS Algorithm: MotivationRLS Algorithm: Motivation Least-squares cost-function & solution non-iterative and
- Gradient Adaptive Lattice (GAL)Gradient Adaptive Lattice (GAL) FIR lattice propagation equations
- Solutions to Problem Set #2 EECE-595, Section II
- Characteristic Functions In class we looked at the notion of the probability density function (PDF)
- Non Uniform Quantization In our previous discussion, we saw that when the input source signal x[n] is
- Joint Statistical Measures Consider a joint experimental venture comprising of two random experi-
- Discrete Random Variables Let X be a discrete random variable that takes integer values xi I with
- -1-2004 MURI Review AERIAL IMAGE OPTIMIZATION IN IMAGINGAERIAL IMAGE OPTIMIZATION IN IMAGING
- Solutions to PS # 2.0 Engineering Problem Solving Using MATLAB
- Sampling of Random Signals In the class we saw an argument from the frequency domain that specified that if we sample a zero-mean,
- Least Squares Lattice (LSL)Least Squares Lattice (LSL) Forward prediction error
- University of New Mexico, Albuquerque Department of Electrical & Computer Engineering
- AFAF--RLS Algorithm: MotivationRLS Algorithm: Motivation Performance of RLS algorithm contingent on choice of
- .@t!@r*F*bars*vtat8iil,l# ,.--4.1i:hit
- IEEE SIGNAL PROCESSING LETTERS, VOL. 11, NO. 2, FEBRUARY 2004 115 A Generalized Normalized Gradient
- Problem Set #3 ECE-595, Section II
- Problem Set #2, MATLAB Assignment ECE-439, Fall 2011
- Problem Set #1 EECE-595, Section II
- r wit'" yl~ding wills.. ~ la) volume flow
- Problem Set #1 ECE-595, Section II
- MULTICOMPONENT SUBSPACE CHIRP PARAMETER ESTIMATION USING DISCRETE FRACTIONAL FOURIER ANALYSIS
- PS #3 , Spring 2012 Digital Signal Processing, ECE-539
- PS #2 , Spring 2012 Digital Signal Processing, ECE-539
- PS #1 , Spring 2012 Digital Signal Processing, ECE-539