Parallel and distributed signal and image integration problems : proceedings of the Indo-US Workshop, Pune, India 16-18 December 1993

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Parallel and distributed signal and image integration problems : proceedings of the Indo-US Workshop, Pune, India 16-18 December 1993

edited, Rabinder N. Madan ... [et al.]

（Series on advances in mathematics for applied sciences）

World Scientific, c1995

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内容説明・目次

内容説明

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, co-ordination, 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.

目次

  • 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.

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