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TSP
2011
230views more  TSP 2011»
13 years 2 months ago
Bayesian Nonparametric Inference of Switching Dynamic Linear Models
—Many complex dynamical phenomena can be effectively modeled by a system that switches among a set of conditionally linear dynamical modes. We consider two such models: the switc...
Emily B. Fox, Erik B. Sudderth, Michael I. Jordan,...
ICASSP
2011
IEEE
12 years 11 months ago
Deconvolution of neuronal signal from hemodynamic response
In this paper we describe a deconvolution technique for obtaining an approximation of the neuronal signal from an observed hemodynamic response in fMRI data. Our approach, based o...
Martin Havlicek, Jirí Jan, Milan Brazdil, V...
NIPS
2000
13 years 9 months ago
Learning Switching Linear Models of Human Motion
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. Effective models of human dynamics can be learned from motion capture data usi...
Vladimir Pavlovic, James M. Rehg, John MacCormick
ICASSP
2011
IEEE
12 years 11 months ago
Closed-form approximation of linear phase IIR digital filters with guaranteed stability
We develop a closed-form approximation algorithm for designing IIR digital filters with linear phase and guaranteed stability. In this algorithm, the stopband and passband edge f...
Masayoshi Nakamoto, Shuichi Ohno
ASPDAC
2010
ACM
119views Hardware» more  ASPDAC 2010»
13 years 5 months ago
VISA: versatile impulse structure approximation for time-domain linear macromodeling
Abstract-- We develop a rational function macromodeling algorithm named VISA (Versatile Impulse Structure Approximation) for macromodeling of system responses with (discrete) time-...
Chi-Un Lei, Ngai Wong