Results 321 to 330 of about 2,461,002 (382)

Exponential Hyperbolic Cosine Robust Adaptive Filters for Audio Signal Processing

IEEE Signal Processing Letters, 2021
In recent years, correntropy-based algorithms which include maximum correntropy criterion (MCC), generalized MCC (GMCC), kernel MCC (KMCC) and hyperbolic cosine function-based algorithms such as hyperbolic cosine adaptive filter (HCAF), logarithmic HCAF (
Krishna Kumar, Rajlaxmi Pandey, Sankha Subhra Bhattacharjee, Nithin V. George   +3 more
semanticscholar   +1 more source

Graphon Filters: Signal Processing in Very Large Graphs

European Signal Processing Conference, 2021
Graph filters are at the core of network information processing architectures, with applications in machine learning and distributed collaborative systems.
Luana Ruiz, Luiz F. O. Chamon, Alejandro Ribeiro   +2 more
semanticscholar   +1 more source

Microelectromechanical filters for signal processing

[1992] Proceedings IEEE Micro Electro Mechanical Systems, 1992
Microelectromechanical filters based on coupled lateral microresonators are demonstrated. This new class of microelectromechanical systems (MEMS) has potential signal-processing applications for filters which require narrow bandwidth (high Q), good signal-to-noise ratio, and stable temperature and aging characteristics.
Liwei Lin, Roger T. Howe, Clark T.-C. Nguyen, Albert P. Pisano   +3 more
openaire   +2 more sources

Analog signal processing/filtering

IEEE Photonic Society 24th Annual Meeting, 2011
Optics has the potential to solve some of the most exciting problems in information systems. It promises crosstalk-free interconnects with essentially unlimited bandwidth, long-distance data transmission without skew and without power- and time-consuming regeneration, miniaturization, parallelism, and efficient implementation of important algorithms ...
Steve Zamek, Dawn T. H. Tan, Yeshaiahu Fainman, Boris Slutsky, L. Fang, Maziar P. Nezhad, Andrew Grieco, Kazuhiro Ikeda   +7 more
openaire   +2 more sources

Kriging filters for multidimensional signal processing

Signal Processing, 2005
The Wiener filter is the well-known solution for linear minimum mean square error (LMMSE) signal estimation. This filter assumes the mean to be known and usually constant. On the other hand, the Kriging filter is an incremental theory, developed within the Geostatistical community, with respect to that of Wiener filters.
Carl-Fredrik Westin, Juan Ruiz-Alzola, Carlos Alberola-López   +2 more
openaire   +2 more sources

Quadratic filters for signal processing

Proceedings of the IEEE, 1992
Polynomial (or Volterra) filters are introduced, and the quadratic filters are presented as the simplest example of such filters. The principle aspects and properties of quadratic filters are derived in the framework of the discrete Volterra expansion. Fixed as well as adaptive filters are considered in one-dimensional and multidimensional environments.
openaire   +3 more sources

Filter morphing for audio signal processing

Proceedings of 1995 Workshop on Applications of Signal Processing to Audio and Accoustics, 2002
The coefficient encoding scheme called "ARMAdillo" for a second order direct form digital filter was previously proposed. We examine the behavior of a second order digital filter, whose coefficients are encoded using the ARMAdillo scheme, when it morphs from one frame to another.
D. Rossum, Yinong Ding
openaire   +2 more sources

Multichannel Signal Processing With Deep Neural Networks for Automatic Speech Recognition

IEEE/ACM Transactions on Audio Speech and Language Processing, 2017
Multichannel automatic speech recognition (ASR) systems commonly separate speech enhancement, including localization, beamforming, and postfiltering, from acoustic modeling.
Tara N. Sainath, Ron J. Weiss, K. Wilson, Bo Li, A. Narayanan, Ehsan Variani, M. Bacchiani, Izhak Shafran, A. Senior, K. K. Chin, Ananya Misra, Chanwoo Kim   +11 more
semanticscholar   +1 more source