Abstract: This paper describes an electrically powered prosthetic system controlled by electromyography (EMG) signal detected from the skin surface of the human body. The research of electrically powered prosthetic systems is divided into two main subjects. One is the design of the joint mechanism. We propose the use of an adaptive joint mechanism based on the tendon-driven architecture. This m...

The complexity of a pattern recognition problem is determined by its representation. It is argued and illustrated by examples that the sampling density of a given dataset and the resulting complexity of a learning problem are inherently connected. A number of criteria are constructed to judge this complexity for the chosen dissimilarity representation. Some nonlinear transformations of the orig...

The diagnostic problems are proposed to be solved via the pattern recognition approach in this paper. The main example has been motivated by an economic macro modelling, hence a reference model approach is adopted in this paper. The dynamic systems under consideration are assumed to be linear in three case studies and non-linear in one case study. All four case studies illustrate the basic conc...

We demonstrate simultaneous prediction of two independent Santa-Fe time series using a single-longitudinal mode semiconductor ring laser with optical feedback. Our results indicate that a prediction with errors comparable to the state-ofthe-art can be achieved for each time series despite the two tasks are computed simultaneously. I by the way that the brain processes the information, computati...

A method for the analysis of transmission electron microscopy diffractograms for determination of the phase contrast transfer function (PCTF) is presented. This is accomplished by pattern recognition methods together with a nonlinear regression method using apriori knowledge about diffractogram shapes and results in an automatic computation of defocus and astigmatism parameters. Other applicati...

An increasing number of computer vision and pattern recognition problems require structured regression techniques. Problems like human pose estimation, unsegmented action recognition, emotion prediction and facial landmark detection have temporal or spatial output dependencies that regular regression techniques do not capture. In this paper we present continuous conditional neural fields (CCNF)...

11 Previous studies on the KIV model outlined a general architecture of modeling sensory– perceptual–intentional action cycle in the primordial vertebrate forebrain using nonlinear dy13 namical principles. KIV consists of three KIII units representing aperiodic/chaotic dynamics in sensory cortex, hippocampal formation, and midline forebrain, respectively. The sensory cortex 15 has demonstrated ...

This paper develops the separating capacities of families of nonlinear decision surfaces by a direct application of a theorem in classical combinatorial geometry. It is shown that a family of surfaces having d degrees of freedom has a natural separating capacity of 2d pattern vectors, thus extending and unifying results of Winder and others on the pattern-separating capacity of hyperplanes. App...

The problem considered in this paper is how to recognize similar objects based on the detection of patterns in pairs of images. This article introduces a new form of classifier based on approximation spaces in the context of near sets for use in pattern recognition. By way of introducing the basic approach, nonlinear diffusion is used for edge detection and object contour extraction. This form ...

In this paper, we introduce heat kernel coupling (HKC) as a method of constructing multimodal spectral geometry on weighted graphs of different size without vertex-wise bijective correspondence. We show that Laplacian averaging can be derived as a limit case of HKC, and demonstrate its applications on several problems from the manifold learning and pattern recognition domain.