Pattern recognition in bistable networks

Date

1999-04-08

Author

VLADIMIR, CHINAROV
Halıcı, Uğur
Leblebicioğlu, Mehmet Kemal

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

245
views

0
downloads

Present study concerns the problem of learning, pattern recognition and computational abilities of a homogeneous network composed from coupled bistable units. An efficient learning algorithm is developed. New possibilities for pattern recognition may be realized due to the developed technique that permits a reconstruction of a dynamical system using the distributions of its attractors. In both cases the updating procedure for the coupling matrix uses the minimization of least-mean-square errors between the applied and desired patterns.

Subject Keywords

Pattern recognition, Learning, Bistable elements, Neural-like network

URI

https://hdl.handle.net/11511/32712

DOI

https://doi.org/10.1117/12.342903

Collections

Department of Electrical and Electronics Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Learning semi-supervised nonlinear embeddings for domain-adaptive pattern recognition Vural, Elif (null; 2019-05-20) We study the problem of learning nonlinear data embeddings in order to obtain representations for efficient and domain-invariant recognition of visual patterns. Given observations of a training set of patterns from different classes in two different domains, we propose a method to learn a nonlinear mapping of the data samples from different domains into a common domain. The nonlinear mapping is learnt such that the class means of different domains are mapped to nearby points in the common domain in order to...
Strengths and weaknesses of problem-based learning in engineeriing education: students’ and tutors’ perspectives Ateş, Özlem; Eryılmaz, Ali (2010-01-01) This study aims to analyze the strengths and weaknesses of problem-based learning (PBL) implementations in engineering education and problems encountered in it from the perspectives of tutors and students. A case study design was employed in this study. To this end, four tutors, their five PBL modules, and fourteen students were selected. The data were collected by means of observations, interviews, and additional data sources. The results indicated that gaining engineer’s viewpoint and self confidence; imp...
Electromagnetic target recognition with the fused MUSIC spectrum matrix method: Applications and performance analysis for incomplete frequency data Secmen, Mustafa; Ekmekci, Evren; Sayan, Gönül (2007-01-01) The aim of this paper is to apply an electromagnetic target recognition method, which is based on the use of fused MUSIC spectrum matrices, to the case of incomplete frequency domain data. The aforementioned method was suggested recently and succesfully applied to both canonical and complicated targets in the presence of complete frequency domain data [1]. However, most of the real world applications involve the use of severely incomplete frequency data, especially missing low frequency information. In this...
Optimum design of flexible multibody systems with dynamic behavior constraints Ider, SK; Oral, Süha (1996-01-01) A methodology is presented for the optimum design of high-speed multibody systems under time-dependent stress and displacement constraints by mathematical programming. Finite elements are used in the modeling of the flexible links. The design variables are the sectional properties of the elements. The time dependence of the constraints is removed through the use oi equivalent constraints based on the most critical constraints. It is shown that this approach yields a better design than using equivalent const...
Almost periodic solutions of recurrently structured impulsive neural networks Top, Gülbahar; Akhmet, Marat; Department of Mathematics (2022-3-28) This thesis aims to conduct detailed and precise neural networks research with impulses at nonprescribed moments in terms of periodic and almost periodic solutions. Most of the actions in nature modeled by neural networks involve repetitions. Hence periodic and almost periodic motions become crucial. So in this thesis, the existence, uniqueness, and stability of the periodic and almost periodic motion are served for the neural networks with prescribed and nonprescribed impacts. This impulsive system is a n...

Citation Formats

C. VLADIMIR, U. Halıcı, and M. K. Leblebicioğlu, “Pattern recognition in bistable networks,” 1999, vol. 3722, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/32712.