Results 211 to 220 of about 303,161 (264)

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.
Juan Ruiz-Alzola, Carlos Alberola-López, Carl-Fredrik Westin   +2 more
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Meridian Filtering for Robust Signal Processing

IEEE Transactions on Signal Processing, 2007
A broad range of statistical processes is characterized by the generalized Gaussian statistics. For instance, the Gaussian and Laplacian probability density functions are special cases of generalized Gaussian statistics. Moreover, the linear and median filtering structures are statistically related to the maximum likelihood estimates of location under ...
Tuncer C. Aysal, Kenneth E. Barner
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Nonlinear Signal Processing Vs. Kalman Filtering

1993 IEEE International Symposium on Circuits and Systems, 2002
A unique and powerful paradigm or methodology for the design of nonlinear dynamical systems and signal processing algorithms is reported. Some aspects of this approach are discussed, and the results of the application of this approach in signal estimation are given.
P. A. Ramamoorthy, Aleksandar Zavaljevski   +1 more
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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.
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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 ...
Y. Fainman, D. Tan, A. Grieco, S. Zamek, K. Ikeda, L. Fang, M. Nezhad, B. Slutsky   +7 more
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Audio signal processing with transversal filters

ICASSP '79. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
A brief introduction to transversal filters is given. Practical aspects of time-domain deconvolution are discussed. Experimental results are included which illustrate transversal-filter phase equalization of bandlimiting filters, analog magnetic recorders, and electroacoustic transducers. A few prospwzective applications are mentioned.
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Signal processing by function elimination filters

ICASSP '76. IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005
In many applications of signal processing (in areas of communication, pattern recognition, measurement) it is necessary to detect (or classify) the signals in the absence of certain a priori information about its parameters. One of the effective methods of solving such problems - the Function Filtration Method - is discussed.
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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.
L. Lin, C.T.-C. Nguyen, R.T. Howe, A.P. Pisano   +3 more
openaire   +1 more source