Signal-processing techniques for localizing an acoustic source buried in noise are tested in a tank experiment. Noise is generated using a discrete source, a bubble generator, and a sprinkler. The experiment has essential elements of a realistic scenario in matched-field processing, including complex source and noise time series in a waveguide with water, sediment, and multipath propagation. The noise-canceling processor is found to outperform the Bartlett processor and provide the correct source range for signal-to-noise ratios below -10 dB. The multivalued Bartlett processor is found to outperform the Bartlett processor but not the noise-canceling processor.
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http://dx.doi.org/10.1121/1.3621059 | DOI Listing |
J Acoust Soc Am
September 2011
Naval Research Laboratory, Stennis Space Center, Mississippi 39529, USA.
Signal-processing techniques for localizing an acoustic source buried in noise are tested in a tank experiment. Noise is generated using a discrete source, a bubble generator, and a sprinkler. The experiment has essential elements of a realistic scenario in matched-field processing, including complex source and noise time series in a waveguide with water, sediment, and multipath propagation.
View Article and Find Full Text PDFIEEE Trans Neural Netw
October 2012
Dept. of Electr. Eng. and Comput. Sci., Korea Adv. Inst. of Sci. and Technol., Daejeon, South Korea.
An field programmable gate array (FPGA) implementation of independent component analysis (ICA) algorithm is reported for blind signal separation (BSS) and adaptive noise canceling (ANC) in real time. In order to provide enormous computing power for ICA-based algorithms with multipath reverberation, a special digital processor is designed and implemented in FPGA. The chip design fully utilizes modular concept and several chips may be put together for complex applications with a large number of noise sources.
View Article and Find Full Text PDFArch Pathol Lab Med
June 2003
Department of Pathology and Molecular Medicine, St Joseph's Healthcare, and McMaster University, Hamilton, Ontario, Canada.
Context: Software that can convert spoken words into written text has been available since the early 1980s. Early continuous speech systems were developed in 1994, with the latest commercially available editions having a claimed accuracy of up to 98% of speech recognition at natural speech rates.
Objectives: To evaluate the efficacy of one commercially available voice-recognition software system with pathology vocabulary in generating pathology reports and to compare this with human transcription.
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