Parallel And Distributed Signal And Image Integration Problems - Proceedings Of The Indo-us Workshop
Will be published approx. on 1. June 1995
Book
Hardback
480 pages
978-981-02-2148-5 (ISBN)
Description
The next generation of engineering and computing systems will be both complex and distributed in functionality due to a variety of information sources needed for their operation. Successful development and deployment of these systems critically depends on the mechanisms for acquisition, coordination, communication and integration of information from various components. This collection of papers addresses various aspects in the area of signal and image integration with a specific emphasis on parallel and distributed solutions. A wide spectrum of issues including image and signal processing, parallel architectures/algorithms, sensor integration/fusion, and neural networks/fuzzy systems, are addressed in various papers.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Professional and scholarly
ISBN-13
978-981-02-2148-5 (9789810221485)
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Schweitzer Classification
Persons
Content
Part 1 Image processing: GMLOS - a robust nonlinear filter for image processing applications, R.L. Kashyap; recursive estimation of higher order rotational motion using quarternions, S.S. Karandikar and S. Choudhury. Part 2 Parallel architectures/algorithms: reconfigurable meshes and image processing, S. Sahni; parallel ray-tracing computations on a network of heterogeneous workstations, M. Padala et al. Part 3 Signal processing: block algorithms for the parametric estimation of signals and systems, R.V. Raja Kumar and A. Mishra; ECG analysis using parametric techniques, L.M. Patnaik et al. Part 4 Sensor integration/fusion: algorithm for resolving inter-dimensional inconsistencies in redundant sensor arrays, R. Brooks and S. Iyengar; fusion rule estimation in multiple sensor systems with unknown noise distributions, N.S.V. Rao. Part 5 Neural networks/fuzzy systems: an artificial neural network model for image reconstruction from multiple frames of noisy sparse data, B. Yegnanarayana and R. Ramaseshan; an experimental character recognition system using neural networks, G. Nagaraja.