Abstract
Suprathreshold stochastic resonance is a variant of stochastic resonance that has been shown to occur in parallel arrays of independently noisy, but otherwise identical, binary threshold devices. It can be described as a form of stochastic signal quantization that utilizes independently random noise sources to digitize an analog signal. This paper outlines a generalization of this effect, and discusses several sensor applications in which it can occur, such as analog-to-digital converter circuits, distributed sensor networks and the reduction of in-band noise via coherent integration in radar, sonar and sodar systems. All of these scenarios can be modeled using a framework called a ‘stochastic pooling network.’
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McDonnell, M.D. (2009). Applying Stochastic Signal Quantization Theory to the Robust Digitization of Noisy Analog Signals. In: In, V., Longhini, P., Palacios, A. (eds) Applications of Nonlinear Dynamics. Understanding Complex Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85632-0_20
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DOI: https://doi.org/10.1007/978-3-540-85632-0_20
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