Recognition of Dynamic Patterns by a Synergetic Computer

Haas, René; Fuchs, Armin; Haken, Hermann; Horvath, Eva A.; Pandya, Abhijit S.; Kelso, J. A. Scott

doi:10.1007/978-3-642-78411-8_8

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…Models of category boundary change that emphasize range-frequency effects (e.g., Parducci, 1965; Parducci & Wedell, 1986) or consistency (Haubensek, 1992) can accommodate a critical-boundary phenomenon as well as the contrastive effects of sequential presentation on category judgments, but they do not predict hysteresis with stimuli of constant range and frequency. Although effects in speech categorization are usually reported to be contrastive, other sorts of category judgments often exhibit hysteresis (Fender & Julesz, 1967; Haas et al, in press; Hock, Kelso, & Schöner, 1993; Kruse & Stadler, 1990; Tuller, Giangrande, Kelso, & Ding, 1993; Williams, Phillips, & Sekuler, 1986).…”

Section: Resultsmentioning

confidence: 99%

“…In the last decade, explicit dynamical models have been formulated to express coordination dynamics governing spontaneous pattern formation across the limbs of an individual (e.g., de Guzman & Kelso, 1991; Haken et al, 1985; Jeka & Kelso, 1989; Kelso, 1981, 1984), between individuals (Schmidt, Carello, & Turvey, 1990), and between individuals and their environment (Kelso, DelColle, & Schöner, 1990; Wimmers, Beek, & van Wieringen, 1992). The concepts have been elaborated to characterize intentional changes in behavior (Kelso, Scholz, & Schöner, 1988; Schöner & Kelso, 1988b), learning (e.g., Kelso, 1990; Schöner, Zanone, & Kelso, 1992; Zanone & Kelso, 1992), development (Thelen, Kelso, & Fogel, 1987; Thelen & Ulrich, 1991), visual perception (Fender & Julesz, 1967; Haas et al, in press; Hock et al, 1993; Kruse & Stadler, 1990; Williams et al, 1986), artificial neural networks for pattern recognition and associative learning (Haken, 1991; Haken, Kelso, Fuchs, & Pandya, 1990; Kawamoto & Anderson, 1985), and human brain activity (Fuchs, Kelso, & Haken, 1992; Kelso, Bressler, et al, 1992).…”

Section: Discussionmentioning

confidence: 99%

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The nonlinear dynamics of speech categorization.

Tuller¹,

Case²,

Ding³

et al. 1994

Journal of Experimental Psychology: Human Perception and Perfor

144

168

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Little is known about the processes underlying the nonlinear relationship between acoustics and speech perception. In Experiment 1, we explored the effects of systematic variation of a single acoustic parameter (silent gap duration between a natural utterance of s and a synthetic vowel ay) on judgements of speech category. The resulting shifts in category boundary between say and stay showed rich dynamics, including hysteresis, contrast, and critical boundary effects. We propose a dynamical model to account for the observed patterns. Experiment 2 evaluated one prediction of the model, that changing the relative stability of the two percepts allows categorical switching. In agreement with the model; an increase in the number of stimulus repetitions maximized the frequency of judgments of category change near the boundary. Thus, a dynamical approach affords the rudiments for a theory of the effects of temporal context on speech categorization.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The nonlinear dynamics of speech categorization.

Tuller¹,

Case²,

Ding³

et al. 1994

Journal of Experimental Psychology: Human Perception and Perfor

144

168

View full text Add to dashboard Cite

show abstract

Self-organization of trajectory formation

Guzman

Kelso

Buchanan

1997

Biological Cybernetics

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Most studies of movement coordination deal with temporal patterns of synchronization between components, often without regard to the actual amplitudes the components make. When such a system is required to produce a composite action that is spatially constrained, coordination persists, but its stability is modulated by spatial requirements effected, we hypothesize, through the component amplitudes. As shown experimentally in part I, when a redundant three-joint system (wrist, elbow, and shoulder) is required to trace a specified arc in space, the joint angles may be frequency- and phased-locked even as the curvature of the trajectory is manipulated. Transitions between joint coordination patterns occur at a critical curvature, accompanied by a significant reduction in wrist amplitude. Such amplitude reduction is viewed as destabilizing the existing coordinative pattern under current task constraints, thereby forcing the joints into a more stable phase relationship. This paper presents a theoretical analysis of these multijoint patterns and proposes an amplitude mechanism for the transition process. Our model uses three linearly coupled, nonlinear oscillators for the joint angles and reproduces both the observed interjoint coordination and component amplitude effects as well as the resulting trajectories of the end effector.

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Recognition of Dynamic Patterns by a Synergetic Computer

Cited by 2 publications

References 15 publications

The nonlinear dynamics of speech categorization.

The nonlinear dynamics of speech categorization.

Self-organization of trajectory formation

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