Results 31 to 40 of about 23,490,234 (337)
Olfactory signal processing [PDF]
Digital Signal Processing, 2016 Olfaction, the sense of smell, has received scant attention from a signal processing perspective in comparison to audition and vision. In this paper, we develop a signal processing paradigm for olfactory signals based on new scientific discoveries including the psychophysics concept of olfactory white.
Lav R. Varshney, Kush R. Varshney
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8th International Multitopic Conference, 2004. Proceedings of INMIC 2004., 2018 In a wireless sensor network, multilevel quantization is necessary to find a compromise between minimizing the power consumption of sensors and maximizing the detection performance at the fusion center (FC).
Thomas J. Cavicchi, U. Spagnolini
semanticscholar +1 more source
Improved quality of experience of reconstructed H.264/AVC encoded video sequences through robust pixel domain error detection [PDF]
, 2008 The transmission of H.264/AVC encoded sequences over noisy wireless channels generally adopt the error detection capabilities of the transport protocol to identify and discard corrupted slices.
Debono, Carl James +2 more
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Applied Signal Processing [PDF]
, 2021 Being an inter-disciplinary subject, Signal Processing has application in almost all scientific fields. Applied Signal Processing tries to link between the analog and digital signal processing domains. Since the digital signal processing techniques have evolved from its analog counterpart, this book begins by explaining the fundamental concepts in ...
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Signal processing with Levy information [PDF]
, 2012 Levy processes, which have stationary independent increments, are ideal for modelling the various types of noise that can arise in communication channels.
Bain A +21 more
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Noise Variance Estimation In Signal Processing [PDF]
, 2007 We present a new method of estimating noise variance. The method is applicable for 1D and 2D signal processing. The essence of this method is estimation of the scatter of normally distributed data with high level of outliers. The method is applicable
Makovoz, David
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Graph Signal Processing for Machine Learning: A Review and New Perspectives [PDF]
IEEE Signal Processing Magazine, 2020 The effective representation, processing, analysis, and visualization of large-scale structured data, especially those related to complex domains, such as networks and graphs, are one of the key questions in modern machine learning.
Xiaowen Dong +4 more
semanticscholar +1 more source
Frame Coherence and Sparse Signal Processing [PDF]
, 2011 The sparse signal processing literature often uses random sensing matrices to obtain performance guarantees. Unfortunately, in the real world, sensing matrices do not always come from random processes.
Bajwa, Waheed U. +2 more
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Structured random measurements in signal processing [PDF]
, 2014 Compressed sensing and its extensions have recently triggered interest in randomized signal acquisition. A key finding is that random measurements provide sparse signal reconstruction guarantees for efficient and stable algorithms with a minimal number ...
Krahmer, Felix, Rauhut, Holger
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Nonlinear signal processing [PDF]
2005 IEEE LEOS Annual Meeting Conference Proceedings, 2005 This paper studies the propagation of femtosecond pulses in a Kerr medium both experimentally and numerically. This work also investigates the similarities between the propagation of light pulses in a Kerr medium and the evolution of fluid dynamical systems, and proposes the use of an optical system to simulate fluid dynamics.
Centurion, Martin +2 more
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