No description available.

No description available.

Estimation fusion, or data fusion for estimation, is the problem of how to best utilize useful information contained in multiple data sets for the purpose of estimating an unknown quantity — a parameter or a process. Estimation fusion with constraints gives rise to challenging theoretical problems given the observations from multiple geometrically dispersed sensors: Under dimensionality constraints, how to preprocess data at each local sensor to achieve the best estimation accuracy at the fusion center? Under communication bandwidth constraints, how to quantize local sensor data to minimize the estimation error at the fusion center? Under constraints on storage, how to optimally update state estimates at the fusion center with out-of-sequence measurements? Under constraints on storage, how to apply the out-of-sequence measurements (OOSM) update algorithm to multi-sensor multi-target tracking in clutter? The present work is devoted to the above topics by applying the best linear unbiased estimation (BLUE) fusion. We propose optimal data compression by reducing sensor data from a higher dimension to a lower dimension with minimal or no performance loss at the fusion center. For single-sensor and some particular multiple-sensor systems, we obtain the explicit optimal compression rule. For a multisensor system with a general dimensionality requirement, we propose the Gauss-Seidel iterative algorithm to search for the optimal compression rule. Another way to accomplish sensor data compression is to find an optimal sensor quantizer. Using BLUE fusion rules, we develop optimal sensor data quantization schemes according to the bit rate constraints in communication between each sensor and the fusion center. For a dynamic system, how to perform the state estimation and sensor quantization update simultaneously is also established, along with a closed form of a recursion for a linear system with additive white Gaussian noise. A globally optimal OOSM update algorithm and a constrained optimal update algorithm are derived to solve one-lag as well as multi-lag OOSM update problems. In order to extend the OOSM update algorithms to multisensor multitarget tracking in clutter, we also study the performance of OOSM update associated with the Probabilistic Data Association (PDA) algorithm.

by Chiu Kim Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1994. / Includes bibliographical references (leaves 103-108). / Chapter Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Speech production --- p.2 / Chapter 1.2 --- Low bit rate speech coding --- p.4 / Chapter Chapter 2 --- Speech analysis & synthesis --- p.8 / Chapter 2.1 --- Linear prediction of speech signal --- p.8 / Chapter 2.2 --- LPC vocoder --- p.11 / Chapter 2.2.1 --- Pitch and voiced/unvoiced decision --- p.11 / Chapter 2.2.2 --- Spectral envelope representation --- p.15 / Chapter 2.3 --- Excitation --- p.16 / Chapter 2.3.1 --- Regular pulse excitation and Multipulse excitation --- p.16 / Chapter 2.3.2 --- Coded excitation and vector sum excitation --- p.19 / Chapter 2.4 --- Multiband excitation --- p.22 / Chapter 2.5 --- Multiband excitation vocoder --- p.25 / Chapter Chapter 3 --- Dual-band and Quad-band excitation --- p.31 / Chapter 3.1 --- Dual-band excitation --- p.31 / Chapter 3.2 --- Quad-band excitation --- p.37 / Chapter 3.3 --- Parameters determination --- p.41 / Chapter 3.3.1 --- Pitch detection --- p.41 / Chapter 3.3.2 --- Voiced/unvoiced pattern generation --- p.43 / Chapter 3.4 --- Excitation generation --- p.47 / Chapter Chapter 4 --- A low bit rate Quad-Band Excitation LSP Vocoder --- p.51 / Chapter 4.1 --- Architecture of QBELSP vocoder --- p.51 / Chapter 4.2 --- Coding of excitation parameters --- p.58 / Chapter 4.2.1 --- Coding of pitch value --- p.58 / Chapter 4.2.2 --- Coding of voiced/unvoiced pattern --- p.60 / Chapter 4.3 --- Spectral envelope estimation and coding --- p.62 / Chapter 4.3.1 --- Spectral envelope & the gain value --- p.62 / Chapter 4.3.2 --- Line Spectral Pairs (LSP) --- p.63 / Chapter 4.3.3 --- Coding of LSP frequencies --- p.68 / Chapter 4.3.4 --- Coding of gain value --- p.77 / Chapter Chapter 5 --- Performance evaluation --- p.80 / Chapter 5.1 --- Spectral analysis --- p.80 / Chapter 5.2 --- Subjective listening test --- p.93 / Chapter 5.2.1 --- Mean Opinion Score (MOS) --- p.93 / Chapter 5.2.2 --- Diagnostic Rhyme Test (DRT) --- p.96 / Chapter Chapter 6 --- Conclusions and discussions --- p.99 / References --- p.103 / Appendix A Subroutine of pitch detection --- p.A-I - A-III / Appendix B Subroutine of voiced/unvoiced decision --- p.B-I - B-V / Appendix C Subroutine of LPC coefficients calculation using Durbin's recursive method --- p.C-I - C-II / Appendix D Subroutine of LSP calculation using Chebyshev Polynomials --- p.D-I - D-III / Appendix E Single syllable word pairs for Diagnostic Rhyme Test --- p.E-I

Thesis (M.S.)--Baylor University, 2005. / Includes bibliographical references (p. 98).

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

ITC/USA 2012 Conference Proceedings / The Forty-Eighth Annual International Telemetering Conference and Technical Exhibition / October 22-25, 2012 / Town and Country Resort & Convention Center, San Diego, California / The U.S. Army Research Laboratory (ARL) is developing an onboard instrument and telemetry system to obtain measurements of the 30mm MK310 projectile's in-flight dynamics. The small size, high launch acceleration, and extremely high rates of this projectile create many design challenges. Particularly challenging is the high spin rate which can reach 1400 Hz at launch. The bandwidth required to continuously transmit solar data using the current method for such a rate would leave no room for data from other sensors. To solve this problem, a data compression scheme is implemented that retains the resolution of the solar sensor data while providing room in the telemetry frame for other measurements.

No description available.

No description available.

Thesis (Ph.D.) -- McMaster University, 1997. / Includes bibliographical references [p. 157-164). Also available via World Wide Web.