Books and Book Chapters

C. R. Johnson, Jr., W. A. Sethares, and A. Klein, Software Receiver Design: Build Your Own Digital Communications System in Five Easy Steps, Cambridge University Press, September, 2011. [Textbook centered on students building a functioning software receiver in Matlab.]

W. A. Sethares, Rhythm and Transforms, Springer Verlag, to appear 2007. [Describes the impact of a “beat finding machine"”on the design of sound processing electronics such as musical synthesizers, drum machines, and special effects devices; provides a concrete basis for a discussion of the relationship between the cognitive processing of temporal information and the mathematical techniques used to describe and understand regularities in data.]

W. A. Sethares, Tuning Timbre Spectrum Scale, Second Edition, Springer Verlag, 2004. [Expanded and revised, even better than before.]

C. R. Johnson, Jr. and W. A. Sethares, Telecommunication Breakdown: Concepts of Communications Transmitted via Software-Defined Radio, Prentice-Hall 2004. [Textbook centered on students building a functioning software receiver in Matlab.]

C. R. Johnson, Jr. and W. A. Sethares, "Connecting Steiglitz-McBride identification, active noise cancellation, and coefficient filtering to a common framework," in Essays in Adaptive Control, Ed. G. Goodwin, Springer-Verlag, 2001. [Trading-off filterings of the regressor vector, the prediction error, the coefficient vector, and/or the update term allows a common analysis, and provides a simple conceptual way of generating 'new' algorithms.]

W. A. Sethares, "Scale," McGraw-Hill Encyclopedia of Science and Technology 9th Edition, 2001. [Print and on-line versions, published in five languages: English, French Italian, Japanese, and Spanish.]

W. A. Sethares, Tuning Timbre Spectrum Scale, Springer Verlag, 1997. [Explores relationships between the spectrum of sounds and the tunings of instruments. In the same way that Western harmonic instruments are related to Western scales, so the nonharmonic spectrum of many nonwestern instruments are related to traditional scales.Develops new tools for sound generation, timbre specification, acoustical signal processing, and musicological analysis.]

W. A. Sethares, "The LMS Family," in Efficient System Identification and Signal Processing Algorithms, Ed. N. Kalouptsidis and S. Theodoridis Springer-Verlag, 1993. [Tutorial about LMS and the signed adaptive variants. Provides an overview of all the major theoretical techniques, with applications in several signal processing areas.]

W. A. Sethares and C. R. Johnson, Jr., "Persistent excitation and robustness in adaptive feedback systems," in Advances in Computation and Communication, Ed. W. A. Porter, Lecture Notes in Control and Information Sciences 130, Springer-Verlag, 1989. [Consolidation and summary of the bursting phenomenon and the use of persistent excitation.]

Refereed Journal Articles

A. Ingle, T. Varghese, and W. A. Sethares, “Efficient 3D reconstruction in ultrasound elastography via a sparse iteration based on Markov random fields,” accepted for publication in IEEE Trans. on Ultrasonics, Ferroelectrics, and Frequency Control, 2017.

C. R. Johnson Jr. and W. A. Sethares, “Canvas Weave Match Supports Designation of Vermeer's Geographer and Astronomer as a Pendant Pair,” JHNA 9:1 (Winter 2017), DOI: 10.5092/jhna.2017.9.1.17

K. Hobby and W. A. Sethares, “Inharmonic strings and the hyperpiano,” Applied Acoustics, Vol. 114, pp. 317–327, Dec. 2016. [Describes a design procedure for musical instruments based on inharmonic (nonuniform) strings.] DOI=10.1016/j.apacoust.2016.07.029

A. Sangari and W. Sethares, “Convergence analysis of two loss functions in soft-max regression,” IEEE Trans. on Signal Processing, Vol. 64, No. 5, pp.1280-1288, March 2016. DOI =10.1109/TSP.2015.2504348

S. Malekpour and W. A. Sethares, “Conditional Granger Causality and Partitioned Granger Causality: Differences and Similarities,” Biological Cybernetics, Volume 109, Issue 6 (2015), Page 627-637, Oct. 2015. doi=10.1007/s00422-015-0665-3

W. A. Sethares and J. Bucklew, “Kernel Techniques for Generalized Audio Crossfades” Cogent Mathematics, Oct. 2015. [A way to conduct audio morphings by imposing a constraint that can be used to smoothly connect different audio spectra by exploiting a formal analogy between the two spatial dimensions of Laplace's partial differential equation and the two dimensions (time and frequency) of a spectrogram.] http://dx.doi.org/10.1080/23311835.2015.1102116

I. Heo and W. A. Sethares, “Classification based on speech rhythm via a temporal alignment of spoken sentences,” IEEE Trans. Audio, Speech and Language Processing. Vol 23, No. 12, Dec. 2015. [A technique called transitive validation is introduced to show that time-varying windowing allows better performance of the speech alignment process than standard fixed window methods.]

C. R. Johnson, Jr., W. A. Sethares, M. H. Ellis, and S. Haqqi, “Hunting for Paper Moldmates Among Rembrandt’s Prints,” IEEE Signal Processing Magazine. June, 2015.

A. Ingle, J. Bucklew, W. A. Sethares, T. Varghese, “Slope Estimation in Noisy Piecewise Linear Functions,” Signal Processing, Vol. 108, 576-588, March 2015.

C. Akkoç, W. A. Sethares and M. K. Karaosmano?lu, “Experiments on the Relationship between Perde and Seyir in Turkish Makam Music,” Music Perception, Vol. 32, No. 4, April 2015. DOI: 10.1525/mp.2015.32.4.322 [A series of experiments demonstrate that it is possible to identify the makam from purely acoustical features, and to establish the relative importance of the various audible features used in this identification.]

V. Chebrolu, D. Saenz, D. Tewatia, W. Sethares, G. Cannon, B. Paliwal, “Rapid Automated Target Segmentation and Tracking on 4D Data without Initial Contours,” Radiology Research and Practice, Volume 2014 (2014), Article ID 5470752014. [Applies classic image processing techniques to 3D motion data for automated segmentation.]

C. R. Johnson, Jr., P. Messier, W. A. Sethares, A. G. Klein, C. Brown, A. H. Do, P. Klausmeyer, P. Abry, S. Jaffard, H. Wendt, S. Roux, N. Pustelnik, N. van Noord, L. van der Maaten, E. Postma. J. Coddington, L. A. Daffner, H. Murata, H. Wilhelm, S. L. Wood, and M. Messier, “Pursuing Automated Classification of Historic Photographic Papers from Raking Light Photographs,” Journal of the American Institute for Conservation, 2014. [Demonstrates that there is enough information in raking light photos to classify photographic paper.]

W. A. Sethares and G. Toussaint, “Expressive Timbre and Timing in Rhythmic Performance: Analysis of Steve Reich’s Clapping Music,” J. New Music Research. Aug. 2014. [Explores the microtiming of events and the microtimbral fluctuations in musical performance.]

M. J. Wu, J. Karls, S. Duenwald-Kuehl, R. Vanderby Jr., and W. A. Sethares, “Spatial and Frequency-Based Super-Resolution of Ultrasound Images,” Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. 2013. [Application of super-resolution to ultrasonic video sequences helps improve the accuracy of strain/stress measurements.]

W. A. Sethares and R. Budney, “Topology of Musical Data,” J. Mathematics and Music 2013. [The musical realm is a particularly promising arena in which to find nontrivial topological features and the analysis uncovers three important topological features: the circle of notes, the circle of fifths, and the rhythmic repetition of timelines. http://arxiv.org/abs/1307.1201]

A. N. Ingle and W. A. Sethares “The least-squares invertible constant Q spectrogram and its application to phase vocoding,” J. of the Acoustical Society of America, 132(2), pp 894-903, Aug 2012. [Presents a LS-invertible variation of the constant-Q transform suitable for phase vocoding applications.]

E. Amiot and W. A. Sethares,, “An Algebra for Periodic Rhythms and Scales” Journal of Mathematics and Music, Vol. 5, No. 3, 2011. [Using circulant scale matrices allows a decomposition of arbitrary scales and rhythms into constituent elements.]

A. Milne and W. A. Sethares,, “Modelling the Similarity of Pitch Collections with Expectation Tensors” Journal of Mathematics and Music, Vol. 5, No. 2, 2011. [Expectation arrays indicate the expected number of tones, ordered pairs of tones, ordered triples of tones, etc., that are heard as having any given pitch.]

W. A. Sethares, A. Milne, S. Tiedje , A. Prechtl and J. Plamondon, “Spectral tools for dynamic tonality and audio morphing” Computer Music Journal, Vol. 33, No. 2, Pages 71-84, Summer 2009. [The Spectral Toolbox is a suite of analysis-resynthesis programs that locate relevant partials of a sound and allow them to be resynthesized at any specified frequencies,. Applications include spectral mappings, spectral morphing, and dynamic tonality.]

R. Arora, W. A. Sethares, and J. Bucklew, “Latent Periodicities in Genome Sequences,” J. Special Topics in Signal Processing Vol. 2, Issue 3, June 2008. [A way to detect latent periodicities in DNA sequences.]

A. Milne, W. A. Sethares, and J. Plamondon, “Tuning Continua and Keyboard Layouts” J. Math and Music Vol. 2, No. 1, March 2008. [The general principles underlying layouts that are invariant in both transposition and tuning.] Author Posting. (c) 'Copyright Holder', 2008.This is the author's version of the work. It is posted here by permission of 'Copyright Holder' for personal use, not for redistribution. The definitive version was published in Journal of Mathematics and Music, Vol 2 Issue 1, March 2008.doi:10.1080/17459730701828677 (http://dx.doi.org/ 10.1080/17459730701828677)

C. Y. Wen, J. K. Chen, and W. A. Sethares, “Asynchronous Two-Way Ranging Using Tomlinson-Harashima Precoding and UWB Signalling,” EURASIP Journal on Wireless Communications and Networking, Vol 2008 (2008), Article ID 436865, 13 pages doi:10.1155/2008/436865. [Generalizes ideas in [54] to handle non-line-of-sight and intersymbol interferences.]

J. Bucklew and W. A. Sethares, “Convergence of a Class of Decentralized Beamforming Algorithms, ” IEEE Trans. Signal Processing, Vol. 56, No. 6, June 2008. [Analysis of algorithms for distributed phase alignment of transmissions in a sensor network.]

A. Milne, W. A. Sethares, and J. Plamondon, “Isomorphic Controllers and Dynamic Tuning— Invariant Fingering Over a Tuning Continuum ” Computer Music Journal, Winter 2007. [A continuous parameter generates a continuum of tunings that can be mapped to a button-field so that the geometric shape of each musical interval is the same within a key, across all keys, and throughout all tunings in the continuum.]

R. Arora and W. A. Sethares, “Adaptive wavetable oscillators,” IEEE Trans. Signal Processing Vol 55, No. 9, Sept 2007. [Adaptive wavetable oscillators separate the detailed shape of the oscillatory waveform from the control signals that specify the phase and frequency. Adaptation allows entrainment to a variety of external inputs.]

C. Y. Wen, R. D. Morris, and W. A. Sethares, “Distance Estimation Using Bidirectional Communications Without Synchronous Clocking,” IEEE Trans. Signal Processing , Vol 55, No. 5, May 2007. [Presents and analyzes a number of methods of distance estimation; the use of bidirectional signaling bypasses the need for accurate synchronous clocking.]

C. Vural, W. A. Sethares, “Convergence analysis of blind image deconvolution via dispersion minimization,” Int. J. Adaptive Control and Signal Processing, 20(7), 321-336, 2006. [Presents conditions on the 2-d dispersion minimization algorithm under which convergence can be guaranteed.]

C. Vural, and W. A. Sethares, “Blind image deconvolution via dispersion minimization,” Digital Signal Processing, 16(2), 137-148, 2006. [This non-recursive version of the 2-d dispersion minimization algorithm is simpler to implement and easier to analyze.]

C. Y Wen, and W. A. Sethares, “Automatic Decentralized Clustering for Wireless Sensor Networks," EURASIP J. Wireless Communication and Networking, 2005:5, pp., 686-697. [It is often more efficient when sensors are clustered into a hierarchy. Here is one way to make this happen without requiring that sensors know their own locations.]

C. Vural and W. A. Sethares, "Recursive blind image deconvolution via dispersion minimization," Int. J. Adaptive Control and Signal Processing, Vol. 19, No. 8, Oct. 2005, pp. 601-622. [Extends the Constant Modulus Algorithm to two dimensions and applies it to the problem of blind image restoration using an autoregressive filter.]

W. Chung, W. A. Sethares, and C. R. Johnson, Jr., “Timing phase offset recovery based on dispersion minimization," IEEE Transactions Signal Processing, Vol. 53, No. 3, March 2005. [Proposes and analyzes a method of blind timing recovery analogous to the constant modulus algorithm used in blind equalization.]

W. A. Sethares, R. D. Morris and J. C. Sethares, "Beat tracking of audio signals using low level audio features," IEEE Trans. On Speech and Audio Processing, Vol. 13, No. 2, March 2005. [Applies a Bayesian particle filter to the problem of finding and tracking beats in a musical performance.]

W. Chung, W. A. Sethares, and C. R. Johnson, Jr., "Performance analysis of blind adaptive phase offset correction based on dispersion minimization," IEEE Transactions Signal Processing, Vol. 52, No. 6 June 2004. [Proposes and analyzes a method of phase offset correction for a wide class of signal constellations and oversampling rates.]

A. M. Bell, W. A. Sethares, and J. A. Bucklew, "Coordination failure as a source of congestion" IEEE Transactions on Signal Processing, Vol. 51. No. 3, March 2003. [Weak convergence analysis of a simple stochastic adaptive algorithm that solves the El Farol problem, emphasizing how agents' uncertainty about the actions of other agents may be a source of congestion in large decentralized systems.]

W. A. Sethares, "Real-time adaptive tunings using MAX" Journal of New Music Research.Vol. 31, No. 4, Dec 2002. [Details the simplifications needed to implement an adaptive tuning algorithm in real time. Introduces the notion of a "context", which imparts a kind of memory to the adaptation.]

R. Martin, J. Balakrishnan, W. A. Sethares, and C. R. Johnson, Jr. "A blind adaptive TEQ for multicarrier systems," IEEE Signal Processing Letters. Nov 2002. [Exploits redundancies in the cyclic prefix to drive the updates of a blind adaptive channel shortening algorithm.]

R. Martin, W. A. Sethares, R. C. Williamson, and C. R. Johnson, Jr, "Exploiting sparsity in adaptive filters", IEEE Transactions on Signal Processing, vol. 50, no. 8, August 2002, pp. 1883-1893. [The "natural gradient" approach is applied to adaptive equalization, resulting in algorithms that can be designed specifically to exploit certain sparsity structures.]

J. Balakrishnan, W. A. Sethares, and C. R. Johnson, Jr., "Approximate channel identification via delta-signed correlation," Int. Journal of Adaptive Control and Signal Processing, May 2002, pp. 309-3223. [Proposes a (numerically) simple procedure for system identification using a modified correlation method.]

W. A. Sethares, "Repetition and Pseudo-Periodicity," Tatra J. Mathematics. December 2001. [The notion of pseudo-periodicity and the related p-norm allow the representation of complex repetitive phenomena as a periodic process plus a set of parameters that define the deviations of that process from true periodicity.]

A. M. Bell and W. A. Sethares, ``Avoiding global congestion using decentralized adaptive agents" IEEE Transactions on Signal Processing, Vol. 49, No. 11, November 2001. [Casti calls the El Farol problem "the most important problem in complex adaptive systems." We argue why he's wrong, by showing that a very simple adaptive "solution" exists to this problem.]

W. A. Sethares and T. W. Staley, "Meter and Periodicity in Musical Performance", Journal of New Music Research, Vol. 30, No. 2, June 2001. [Preprocessing the audio signal with a psychoacoustically motivated method of data reduction allows application of the Periodicity Transforms to the problem of rhythm and meter determination.]

C. A. Jacobson, C. R. Johnson, Jr., D. C. McCormick, W. A. Sethares, "Stability of active noise control algorithms," IEEE Signal Processing Letters, vol. 8, no. 3, March 2001. [Conducts a stability analysis of active noise control algorithms by showing that the adapted models have more in common with nonlinear FIR equation error models than with the IIR output error models they superficially resemble.]

W. A. Sethares and T. W. Staley, "Periodicity Transforms", IEEE Transactions on Signal Processing, vol. 47, no. 11, 2953-2964, Nov. 1999. [Introduces a method of detecting periodicities in data that exploits a series of projections onto "periodic subspaces." The algorithm finds its own set of nonorthogonal basis elements (based on the data), rather than assuming a fixed predetermined basis as in standard transforms.]

W. A. Sethares, "Consonance based spectral mappings," Computer Music Journal 22:1, 56-72, Spring 1998. [Presents a method of mapping the spectrum of a sound so as to make it consonant with a given specified reference spectrum. One application is to transform nonharmonic sounds into harmonic equivalents. Alternatively, it can be used to create nonharmonic instruments that retain the tonal qualities of familiar (harmonic) instruments. Musical uses of such timbres is discussed, and new forms of (nonharmonic) modulation are introduced. A series of sound examples demonstrate both the breadth and limitations of the method]

R. Sharma, W. A. Sethares, and J. A. Bucklew, "Analysis of momentum adaptive filtering algorithms," IEEE Transactions on Signal Processing, vol. 46, no.5, 1430-1434, May 1998. [Generalizes the weak convergence framework to deal with non-identity transition matrices, and applies this to "momentum" algorithms. The effects of momentum on both stability and asymptotic convergence are characterized concretely.]

K. L. Blackmore, R. C. Williamson, I. M. Y. Mareels, and W. A. Sethares, "Online Learning via Congregational Gradient Descent," Mathematics of Controls, Systems, and Signals 10:(4) 331-363, 1997. [Proposes and examines a populational based gradient algorithm that can be guaranteed to converge to the global minimum. Estimates of size of optimal population are obtained via a deterministic averaging approach.]

W. A. Sethares, ``Specifying Spectra for Musical Scales," J. of the Acoustical Society of America in 102(4), Oct. 1997. [Presents a method of specifying the spectrum of a sound so as to maximize a measure of consonance with a given desired scale.] *

R. Sharma, W. A. Sethares, and J. A. Bucklew, "Stochastic analysis of the SD modulator and differential pulse code modulator," IEEE Transactions on Circuits and Systems, vol. 44, no.10, Oct. 1997. [Generalizes and applies the weak connvergence framework to various kinds of modulators. The effects of various input densities are characterized concretely.]

K. Benson and W. A. Sethares, ``Spectral peak detection and control," IEEE Transactions on Signal Processing, vol. 45, no. 10, Oct. 1997. [A method of detecting spectral peaks as they form in an adaptive filter and a method to control them.]

J. Sankey and W. A. Sethares, "A consonance-based approach to the harpsichord tuning of Domenico Scarlatti," J. of the Acoustical Society of America, April, 1997. [Applies psychoacoustic measure of "total dissonance" to the problem of reconstructing musical scales that best fit the extant work of Scarlatti.] *

R. Sharma, W. A. Sethares, and J. A. Bucklew, "Analysis of stochastic gradient based adaptive filtering algorithms with general cost function," IEEE Transactions on Signal Processing. vol. 44, no. 9, Sept. 1996. [Analyzes stochastic gradient algorithms with general cost functions and gives asymptotic distibutions for leaky LMS, momentum algorithms, quantized state algorithms, and LMF.]

Chi-Chin Chou and W. A. Sethares, "Multiplication-free evaluation of polynomials via a Stochastic Bernstein Representation," Applied Mathematics and Computation. vol. 79, no. 1, pp. 2-25, Sept. 1996. [A new method for multiplication-free evaluation of polynomials is proposed. The Stochastic Bernstein Representation is a cellular automata like data structure capable of representing any continuous function arbitrarily closely, and an error bound is given using a large deviations technique.]

H. E. Liao and W. A. Sethares, "Cross-term analysis of LNL models," IEEE Trans. on Circuits and Systems. vol. 43, no. 4, April 1996. [Use of dispersion functions to determine structural properties of nonlinear models, focusing on those which can be described as a static nonlinearity sandwiched between two linear dynamic systems.]

J. Gronquist, W. A. Sethares, F. L. Alvarado, "Animated Vectors for the Visualization of Power System Phenomena," IEEE Transactions on Power Systems, vol. 11, no. 1, pp. 267-273, Feb. 1996. [Introduces a new (exact) mechanical analog for power systems that can be easily animated to demonstrate important issues in power systems design and control, including load flows, dynamic stability, islanding, use of FACTS devices, and dispatch options.]

J. F. Gronquist, W. A. Sethares, F. L. Alvarado, and R. H. Lasseter, "Power oscillation damping control strategies for FACTS devices using locally measurable quantities," IEEE Transactions on Power Systems. vol. 10, no. 3, pg. 1598-1606, Aug. 95. [Derives Lyapunov based control strategies for power oscillation damping of a variety of FACTS devices. The controllers require only information available at the bus at which the device is installed.]

H. E. Liao and W. A. Sethares, "Suboptimal identification of nonlinear ARMA models using an orthogonality approach," IEEE Trans. on Circuits and Systems. vol. 42, no. 1, pg. 14-22, Jan. 95. [Uses "dispersion functions" for a correlation-style analysis that is applicable to the identification of nonlinear systems.]

M. Niedzwiecki and W. A. Sethares, "Smoothing of discontinuous signals: the competitive approach," IEEE Trans. on Signal Processing, vol. 43, no. 1, pg. 1-12, Jan. 95. [A new approach to the smoothing of discontinuous signals is suggested. The approach is justified by an extension of the Kalman filter to the nonlinear case.]

W. A. Sethares and J. A. Bucklew, "Local stability of the median LMS filter," IEEE Trans. on Signal Processing, vol. 42, no. 11, pg. 2901-2906, Nov. 94. [Applies stochastic averaging theory to the median filter provides firm conditions for stability and instability.]

J. A. Bucklew and W. A. Sethares, "The covering problem and m-dependent adaptive algorithms," IEEE Trans. on Signal Processing vol. 42, no. 10, pg. 2616-2627, Oct. 94. [Adaptive filtering algorithms applied to the problem of learning nonlinear decision regions. Stochastic averaging theory is generalized to consider stepsize dependent nonlinearities, and is then applied to prove local stability of the proposed algorithms.]

S. Vembu, S. Verdu, R. A. Kennedy, and W. A. Sethares, "Convex cost functions in blind equalization," IEEE Trans. on Signal Processing vol. 42, no. 8, pg. 1952-1960, August 1994. [The blind equalization problem attempts system identification without access to the true inputs. This paper asks the question: what are sensible cost functions for blind equalization? Behavioral aspects of these choices are examined.]

W. A. Sethares, "Adaptive tunings for musical scales," Journal of the Acoustical Society of America, vol. 96, no. 1, pg. 10-19, July 1994. [Describes an adaptive, consonance based approach to the problem of forming scales that can match a desired set of intervals and can simultaneously be modulated to all keys. One reviewer stated that this paper "sweeps away about five centuries of useless arguments about scales."] *

L. Yao and W. A. Sethares, "Nonlinear parameter estimation via the genetic algorithm" IEEE Trans. on Signal Processing, vol. 42, no. 4, April 1994. [The genetic algorithm is modified to attack the problem of identification of parameters in nonlinear systems. The convergence of the modified algorithm is analyzed. This explains why earlier attempts at use of the genetic algorithm in system identification failed.]

L. Yao, W. A. Sethares and D. C. Kammer, "Sensor placement for on-orbit modal identification of large space structures via a genetic algorithm," Journal of the American Institute of Aeronautics and Astronautics, vol. 31, no. 10, Oct. 1993. [Solving the modal identification problem with the genetic algorithm gives better answers than any of the competing suboptimal methods, at the expense of a larger computational burden.]

W. A. Sethares, "Local consonance and the relationship between timbre and scale," Journal of the Acoustical Society of America. vol. 94, no. 3, pp. 1218-1228, Sept. 1993. [An explicit parameterization of Plomp and Levelt's consonance curve leads to a family of optimization problems which are used to answer two complementary issues: Given a scale, what timbre is most appropriate? Given a timbre, what scale is most appropriate?]*

J. A. Bucklew, T. Kurtz and W. A. Sethares, "Weak convergence and local stability properties of fixed stepsize recursive algorithms," IEEE Trans. on Information Theory, vol. 39, no. 3, May 1993. [Conditions for stability of the sign-sign LMS algorithm had eluded researchers for years. This paper derives the stability conditions and presents a powerful methodology (stochastic ODE's) for analyzing arbitrary small stepsize algorithms.]

D. A. Lawrence, W. A. Sethares and W. Ren, "Parameter drift instability in adaptive feedback systems," IEEE Trans. on Automatic Control. vol. 38, no. 4, April 1993. [Several authors had conjectured a global stability (or "self stabilization") of output error adaptive algorithms. This paper shows irrevocably that such algorithms are not globally bounded.]

G. A. Williamson, P. Clarkson, and W. A. Sethares, "Performance characteristics of the adaptive median LMS filter, IEEE Trans. on Signal Processing, vol. 41, no. 2, pp. 667-680, Feb. 1993. [The median LMS is proposed to reduce the effects of input noise and to adapt more intelligently in an impulsive environment. Analysis and simulations demonstrate this to be a powerful new adaptive technique.]

W. A. Sethares, "Adaptive algorithms with nonlinear data and error functions," IEEE Trans. on Signal Processing, vol. 40, no. 9, pp. 2199-2206, Sept. 1992. [Provides generic counterexample to stability of all LMS variants with nonlinearities applied to regressor.]

W. A. Sethares and J. Bucklew, "Excursions of adaptive algorithms via the poisson clumping heuristic," IEEE Trans. on Signal Processing, vol. 40, no. 6, pp. 1443-1451, June 1992. [Examination of long term behavior of LMS variants. For large excursions, algorithms are asymptotically Poisson distributed. Gives estimates of expected time to failure of adaptive control systems.]

G. L. Skibinski and W. A. Sethares, "Thermal parameter estimation using recursive identification," IEEE Trans. on Power Electronics, vol. 6, no. 2, pp. 228-239, April 1991. [Application of (real time, adaptive) system identification to the problem of thermal estimation in semiconductors. Replaces a graphical method of thermal design that has been in place since the mid 60's. Conference version of paper wins best paper award at IEEE Industrial Applications Society meeting in 1990.]

W. A. Sethares and I. M. Y. Mareels, "Dynamics of an adaptive hybrid," IEEE Trans. on Circuits and Systems, vol. 38, no. 1, pp. 1-11, Jan. 1991. [First demonstration that the bursting of hybrids is due to a bifurcation in the underlying adaptive system. Chaotic dynamics revealed. Argues that this is the cause of bursting in virtually all adaptive systems where the adaptive element lies inside a feedback loop.]

Z. Ding, C. R. Johnson, Jr., and W. A. Sethares, "Frequency dependent bursting in adaptive echo cancellation and its prevention using double talk detectors," Int. Journal of Adaptive Control and Signal Processing, vol. 4, pg. 219-236, 1990. [A possible solution to the bursting problem in adaptive hybrids. Proposes a new "double talk detector" that uses available information to squelch "bursts."]

W. A. Sethares, B. D. O. Anderson, C. R. Johnson, Jr., "Adaptive Algorithms with Filtered Regressor and Filtered Error," Mathematics of Control, Signals, and Systems, 2:381-403, 1989. [This study amalgamates virtually all known adaptive algorithms (with linear filters on error and regressor) into a simple generic form. Uses averaging theory to derive concrete expressions for behavior, especially stability.]

W. A. Sethares, C. R. Johnson, Jr., C. Rohrs, "Bursting in Adaptive Hybrids," IEEE Trans. on Communications, vol. 37, no. 8, pp. 791-799, Aug. 1989. [When an adaptive algorithm is placed inside a feedback loop, the potential for instability exists. This paper demonstrates that the bursting phenomenon (first encountered by Anderson) is generic to such systems, and is not a unique feature of adaptive control. Points towards possible solutions in the hybrid case.]

C. R. Elevitch, W. A. Sethares, and C. R. Johnson, Jr., "Quiver Diagrams for Signed Adaptive Algorithms," IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. 37, no. 2, pp. 227-235, Feb. 1989. [Signed IIR algorithms explored in terms of a geometric criterion. Raises important general questions for communication standards such as ADPCM.]

W. A. Sethares and C. R. Johnson, Jr., "A Comparison of Two Quantized State Adaptive Algorithms," IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. 37, no. 1, pp. 138-143, Jan. 1989. See also "Reply to Comments on 'A comparison of two quantized state adaptive algorithms,'" vol. 42, no. 3, pp. 673, March 1994. [Lyapunov-style proof of stability of quantized-error algorithm contrasts with averaging results for quantized-regressor algorithm. Helps to determine which algorithm is most appropriate in a given application.]

C. R. Johnson, Jr., S. Dasgupta, and W. A. Sethares, "Averaging Theory for Proof of Local Stability of Real CMA," IEEE Trans. on Acoustics, Speech, and Signal Processing, vol. 36, no. 6, pp. 900-910, June 1988. [Averaging applied to the Constant Modulus Algorithm; gives first theoretical demonstration of when and why this algorithm "works."]

W. A. Sethares, I. M. Y. Mareels, B. D. O. Anderson, C. R. Johnson, Jr., "Excitation Conditions for Sign-Regressor LMS," IEEE Trans. on Circuits and Systems, vol. 35, no. 6, pp. 613-624, June 1988. [Conditions under which sign-regressor LMS algorithm will diverge. Lays to rest a long standing discussion in the literature regarding sign LMS. Use of deterministic averaging theory.]