Task Dependence of Perceptual Deadzone

Support-Vector Networks

Abstract: The support-vector network is a new learning machine for two-group classification problems. The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space. In this feature space a linear decision surface is constructed. Special properties of the decision surface ensures high generalization ability of the learning machine. The idea behind the support-vector network was previously implemented for the restricted case where the training data can be separated without errors. We here extend this result to non-separable training data. High generalization ability of support-vector networks utilizing polynomial input transformations is demonstrated. We also compare the performance of the support-vector network to various classical learning algorithms that all took part in a benchmark study of Optical Character Recognition.

Psychophysics: The Fundamentals

Abstract: Contents: Preface. Psychophysical Measurement of Thresholds: Differential Sensitivity. Psychophysical Measurement of Thresholds: Absolute Sensitivity. The Classical Psychophysical Methods. Classical Psychophysical Theory. The Theory of Signal Detection. Further Considerations of TSD. Procedures of TSD. Some Applications of TSD. The Measurement of Sensory Attributes and Discrimination Scales. Partition Scales. Psychophysical Ration Scaling. Evaluation of Ratio Scaling Methods. The Psychophysical Law. Some Fundamental Issues in Psychophysical Scaling.

Haptic perception: a tutorial.

Abstract: This tutorial focuses on the sense of touch within the context of a fully active human observer. It is intended for graduate students and researchers outside the discipline who seek an introduction to the rapidly evolving field of human haptics. The tutorial begins with a review of peripheral sensory receptors in skin, muscles, tendons, and joints. We then describe an extensive body of research on “what” and “where” channels, the former dealing with haptic perception of objects, surfaces, and their properties, and the latter with perception of spatial layout on the skin and in external space relative to the perceiver. We conclude with a brief discussion of other significant issues in the field, including vision-touch interactions, affective touch, neural plasticity, and applications.

Adaptive procedures in psychophysical research.

Abstract: As research on sensation and perception has grown more sophisticated during the last century, new adaptive methodologies have been developed to increase efficiency and reliability of measurement. An experimental procedure is said to be adaptive if the physical characteristics of the stimuli on each trial are determined by the stimuli and responses that occurred in the previous trial or sequence of trials. In this paper, the general development of adaptive procedures is described, and three commonly used methods are reviewed. Typically, a threshold value is measured using these methods, and, in some cases, other characteristics of the psychometric function underlying perceptual performance, such as slope, may be developed. Results of simulations and experiments with human subjects are reviewed to evaluate the utility of these adaptive procedures and the special circumstances under which one might be superior to another.

Sequential effects in judgments of loudness

Abstract: A multiple regression analysis of sequential effects in magnitude estimation and absolute identification is presented as an alternative to the approach used by Lockhead and his students. The new analysis indicates that sequential effects do not extend over more than one trial. This is in agreement with the response ratio hypothesis. A more detailed multiple regression analysis of these sequential effects indicates that the magnitude of the correlation between successive responses is heavily dependent on the decibel difference between successive signals. This is not in agreement with the response ratio hypothesis, and the hypothesis is reformulated to take account of this finding. This modification of the model is tested by comparing distributions of normalized responses to theoretical distributions suggested by the model and to a possible alternative distribution. Language: en