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ACOUSTIC TRANSDUCER ARRAY SIGNAL PROCESSING

The Journal of the Acoustical Society of America, 2012
A set of filters is configured to distribute input signals representing a single perceptual axis to first and second physically separate arrays (10OL, 100R) of loudspeakers comprising at least first and second transducers (104, 106, 108, 110), such that the arrays of loudspeakers will create an array pattern corresponding to the input signals when the ...
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Array signal processing using digital subarrays

IET International Conference on Radar Systems 2007, 2007
Subarrays constitute a step in the direction towards full digitisation of array antennas. An overview of the problems of digital processing with subarray outputs and a description of several mitigation techniques is given. We present rules for designing subarrays, for forming sum and difference beams, clusters of scanned beams at subarray level, and ...
U. Nickel   +3 more
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On Performance of Array Signal Processing

IEEE Journal of Oceanic Engineering, 1987
A unified treatment for performance evaluation of various array signal processors is presented. Detection performance is expressed in terms of the parameter of the power-type receiver operating characteristic (ROC) for optimum, beamformer, and null-steerer detectors.
L. Nolte   +2 more
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Bilinear signal synthesis in array processing

IEEE Transactions on Signal Processing, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Mu, Weifeng.   +2 more
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Trends in array signal processing

Sixth Multidimensional Signal Processing Workshop, 2003
Summary form only given, as follows. Arrays and associated signal processing algorithms have been in use for many years. In recent years, a new wave of algorithms has swept upon the scene promising superior performance at the expense of computational load. Rather than a litany of unrelated algorithms, these new approaches are based on a small number of
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Compressive sensing for array signal processing

2012 Annual IEEE India Conference (INDICON), 2012
Compressive sensing (CS) is an emerging area in which the conventional two step process of data acquisition and compression can be integrated into a single step. Compressive sensing exploits the sparsity of a signal and allows the digital signal to be reconstructed from far fewer measurements than the original size of the signal.
B. Anila Satheesh   +3 more
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Optimum array filters for array data signal processing

IEEE Transactions on Acoustics, Speech, and Signal Processing, 1983
This paper deals with the design of filters for processing data obtained from arrays of sensors used for signal measurements in a variety of applications. The objective of the filters is to optimally suppress undesired signals intercepting the array, while at the same time to preserve the desired signal that the array is attempting to measure.
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Array signal processing under model uncertainties

1991 IEEE International Symposium on Circuits and Systems (ISCAS), 1991
Three array signal processing model error scenarios are considered: errors in sensor gains and phases, errors in sensor location, and errors in sensor-pair alignments of ESPRIT-type subarrays. The array models under the latter two error scenarios are shown to be approximately of the same form as that under sensor gains and phases provided that the ...
V.C. Soon, L. Tong, Y.F. Huang, R. Liu
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Event-Based Phased Array Signal Processing

Structural Health Monitoring 2019, 2019
In the last few years video-based techniques for identifying the dynamic properties of structures have become of increasing interest. These techniques offer the possibility of capturing high-resolution structural dynamics information at very low cost. In recent years event-based imaging technology has also become commercially available.
MOISÉS SILVA   +3 more
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Some aspects of array signal processing

IEE Proceedings F Radar and Signal Processing, 1992
The paper presents an overview of some important aspects of array signal processing in the context of narrowband applications. Inverse methods for solving the array signal processing problem are reviewed. Two case studies are presented, to illustrate the various issues discussed here.
S. Haykin   +3 more
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