Probabilistic characterization and synthesis of complex driven systems

Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.

Bibliographic Details
Main Author: Schoner, Bernd, 1969-
Other Authors: Neil A. Gershenfeld.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2011
Subjects:
Online Access:http://hdl.handle.net/1721.1/62352
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author Schoner, Bernd, 1969-
author2 Neil A. Gershenfeld.
author_facet Neil A. Gershenfeld.
Schoner, Bernd, 1969-
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description Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000.
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spelling mit-1721.1/623522019-04-10T21:38:05Z Probabilistic characterization and synthesis of complex driven systems Schoner, Bernd, 1969- Neil A. Gershenfeld. Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences. Massachusetts Institute of Technology. Dept. of Architecture. Program In Media Arts and Sciences. Architecture. Program In Media Arts and Sciences. Thesis (Ph.D.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2000. Includes bibliographical references (leaves 194-204). Real-world systems that have characteristic input-output patterns but don't provide access to their internal states are as numerous as they are difficult to model. This dissertation introduces a modeling language for estimating and emulating the behavior of such systems given time series data. As a benchmark test, a digital violin is designed from observing the performance of an instrument. Cluster-weighted modeling (CWM), a mixture density estimator around local models, is presented as a framework for function approximation and for the prediction and characterization of nonlinear time series. The general model architecture and estimation algorithm are presented and extended to system characterization tools such as estimator uncertainty, predictor uncertainty and the correlation dimension of the data set. Furthermore a real-time implementation, a Hidden-Markov architecture, and function approximation under constraints are derived within the framework. CWM is then applied in the context of different problems and data sets, leading to architectures such as cluster-weighted classification, cluster-weighted estimation, and cluster-weighted sampling. Each application relies on a specific data representation, specific pre and post-processing algorithms, and a specific hybrid of CWM. The third part of this thesis introduces data-driven modeling of acoustic instruments, a novel technique for audio synthesis. CWM is applied along with new sensor technology and various audio representations to estimate models of violin-family instruments. The approach is demonstrated by synthesizing highly accurate violin sounds given off-line input data as well as cello sounds given real-time input data from a cello player. by Bernd Schoner. Ph.D. 2011-04-25T15:45:35Z 2011-04-25T15:45:35Z 2000 2000 Thesis http://hdl.handle.net/1721.1/62352 48591202 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 204 leaves application/pdf Massachusetts Institute of Technology
spellingShingle Architecture. Program In Media Arts and Sciences.
Schoner, Bernd, 1969-
Probabilistic characterization and synthesis of complex driven systems
title Probabilistic characterization and synthesis of complex driven systems
title_full Probabilistic characterization and synthesis of complex driven systems
title_fullStr Probabilistic characterization and synthesis of complex driven systems
title_full_unstemmed Probabilistic characterization and synthesis of complex driven systems
title_short Probabilistic characterization and synthesis of complex driven systems
title_sort probabilistic characterization and synthesis of complex driven systems
topic Architecture. Program In Media Arts and Sciences.
url http://hdl.handle.net/1721.1/62352
work_keys_str_mv AT schonerbernd1969 probabilisticcharacterizationandsynthesisofcomplexdrivensystems