Adaptive Filtering Techniques

This research focuses on adaptive signal processing, where neural networks are used to filter and estimate sensory input. It emphasizes the development of algorithms that adapt to changing signals and environments.

adaptive filtering
signal processing
neural estimation
connectivity patterns
Bayesian methods

690 papers

Parent topic: Neural Network Architectures and Techniques

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Papers Over Time

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Top Papers

Sniffing Controls An Adaptive Filter Of Sensory Input To The Olfactory Bulb

2007 · 350 citations

Estimation Of Time-Varying Connectivity Patterns Through The Use Of An Adaptive Directed Transfer Function

2008 · 142 citations

Nonlinear Bayesian State Estimation: A Review Of Recent Developments

2012 · 136 citations

Face Identification Using One Spike Per Neuron: Resistance To Image Degradations.

2001 · 113 citations

Signal Detection With Criterion Noise: Applications To Recognition Memory.

2009 · 108 citations

State-dependent Spike Detection: Concepts And Preliminary Results.

1991 · 94 citations

Recursive Gaussian Derivative Filters

0 · 90 citations

Identification Of Bursts In Spike Trains

0 · 86 citations

Nonlinear Autoregressive Processes

1978 · 85 citations

Inference Of A Nonlinear Stochastic Model Of The Cardiorespiratory Interaction

2005 · 78 citations

Shapes Of Derivative Neopolarograms

1977 · 67 citations

Olfactory Bulb Coding Of Odors, Mixtures And Sniffs Is A Linear Sum Of Odor Time Profiles

2015 · 63 citations

A Class Of Convolution-Based Models For Spatio-Temporal Processes With Non-Separable Covariance Structure

2010 · 58 citations

Re-Identification In The Function Space Of Feature Warps

2015 · 56 citations

Storage Of A Temporal Pattern Sequence In A Network

1982 · 50 citations

From Birdsong To Human Speech Recognition: Bayesian Inference On A Hierarchy Of Nonlinear Dynamical Systems

2013 · 46 citations

Approaches To Biological Information Processing: Physics And Mathematics Of The Nervous System . Proceedings Of A Summer School, Trieste, Italy, Aug. 1973. M. Conrad, W. Güttinger, And M. Dal Cin, Eds. Springer-Verlag, New York, 1974. Xiv, 584 Pp., Illus. Paper, $18.50. Lecture Notes In Mathematics, Vol. 4.

1975 · 46 citations

A Neural Model Of High-Level Motion Processing: Line Motion And Formotion Dynamics.

1997 · 44 citations

Functional Approximation Of Impulse Responses

2018 · 43 citations

Thresholds And Smooth Transitions In Vector Autoregressive Models

2013 · 42 citations