Kalman Filtering and Neural Networks

Authors:
Simon S. Haykin
Affiliations:
-
Venue:
Kalman Filtering and Neural Networks
Year:
2001

Citing 0
Cited 72

Learning Context Sensitive Languages with LSTM Trained with Kalman Filters

ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Kalman filters improve LSTM network performance in problems unsolvable by traditional recurrent nets

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Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks

Neural Networks - 2003 Special issue: Advances in neural networks research — IJCNN'03
A fast fading channel identification method for OFDM communication system

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An Augmented Extended Kalman Filter Algorithm for Complex-Valued Recurrent Neural Networks

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Kalman filtering for neural prediction of response spectra from mining tremors

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Building Blocks for Variational Bayesian Learning of Latent Variable Models

The Journal of Machine Learning Research
Application of the evidence procedure to the estimation of wireless channels

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Learning and approximate inference in dynamic hierarchical models

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Implicit 3D modeling and tracking for anywhere augmentation

Proceedings of the 2007 ACM symposium on Virtual reality software and technology
Sequential Bayesian kernel modelling with non-Gaussian noise

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Error-driven active learning in growing radial basis function networks for early robot learning

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Radial basis function networks for wind speed prediction

AIKED'06 Proceedings of the 5th WSEAS International Conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Gaussian process product models for nonparametric nonstationarity

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Automated cross-modal mapping in robotic eye/hand systems using plastic radial basis function networks

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Mining Data from a Metallurgical Process by a Novel Neural Network Pruning Method

ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II
Neural Network Training with Extended Kalman Filter Using Graphics Processing Unit

ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
Social coordination in toddler's word learning: interacting systems of perception and action

Connection Science - Social Learning in Embodied Agents
Nonlinear Bayesian Filters for Training Recurrent Neural Networks

MICAI '08 Proceedings of the 7th Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
A novel fast Kolmogorov's spline complex network for pattern detection

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The perception loop in CiceRobot, a museum guide robot

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A novel fast Kolmogorov's spline complex network for pattern detection

SMO'08 Proceedings of the 8th conference on Simulation, modelling and optimization
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Experiments and Reference Models in Training Neural Networks for Short-Term Wind Power Forecasting in Electricity Markets

IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
Using Kalman-Filtered Radial Basis Function Networks to Forecast Changes in the ISEQ Index

Proceedings of the 2007 EvoWorkshops 2007 on EvoCoMnet, EvoFIN, EvoIASP,EvoINTERACTION, EvoMUSART, EvoSTOC and EvoTransLog: Applications of Evolutionary Computing
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Discovering time differential law equations containing hidden state variables and chaotic dynamics

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A growing and pruning method for radial basis function networks

IEEE Transactions on Neural Networks
Sequential non-stationary dynamic classification with sparse feedback

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Identification of a class of nonlinear systems by a continuous-time recurrent neurofuzzy network

ACC'09 Proceedings of the 2009 conference on American Control Conference
Discrete-time decentralized neural block controller for a five DOF robot manipulator

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High order neural networks for wind speed time series prediction

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Real-time decentralized neural block controller for a robot manipulator

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Letters: Efficient online recurrent connectionist learning with the ensemble Kalman filter

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Application of neural network to the alignment of strapdown inertial navigation system

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Black-box identification of a class of nonlinear systems by a recurrent neurofuzzy network

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Memory-efficient fully coupled filtering approach for observational model building

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Social action tracking via noise tolerant time-varying factor graphs

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Unscented feature tracking

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Improved fractional Kalman filter and its application to estimation over lossy networks

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Recursive inverse adaptive filtering algorithm

Digital Signal Processing
SEAL: soft error aware low power scheduling by Monte Carlo state space under the influence of stochastic spatial and temporal dependencies

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Active data collection for efficient estimation and comparison of nonlinear neural models

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Schur Complement Preconditioners for Surface Integral-Equation Formulations of Dielectric Problems Solved with the Multilevel Fast Multipole Algorithm

SIAM Journal on Scientific Computing
Long-Term prediction of time series using state-space models

ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part II
Adaptive point-cloud surface interpretation

CGI'06 Proceedings of the 24th international conference on Advances in Computer Graphics
SETS: stochastic execution time scheduling for multicore systems by joint state space and Monte Carlo

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Coupling time decoding and trajectory decoding using a target-included model in the motor cortex

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Recurrent networks for integrated navigation

ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part III
SCALETRACK: a system to discover dynamic law equations containing hidden states and chaos

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A new extension of kalman filter to non-gaussian priors

ICVGIP'06 Proceedings of the 5th Indian conference on Computer Vision, Graphics and Image Processing
Wavelet neural network algorithms with applications in approximation signals

MICAI'11 Proceedings of the 10th international conference on Artificial Intelligence: advances in Soft Computing - Volume Part II
Decentralized neural identifier and control for nonlinear systems based on extended Kalman filter

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2012 Special Issue: A novel extended kernel recursive least squares algorithm

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Kalman filtering strategies utilizing the chattering effects of the smooth variable structure filter

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Tracking of multiple targets using on-line learning for appearance model adaptation

ICIAR'07 Proceedings of the 4th international conference on Image Analysis and Recognition
Discrete-time inverse optimal neural control for synchronous generators

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Empirical modeling of renal motion for improved targeting during focused ultrasound surgery

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Dynamic stochastic blockmodels: statistical models for time-evolving networks

SBP'13 Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction
Extended Kalman filter-based Elman networks for industrial time series prediction with GPU acceleration

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Selective Recurrent Neural Network

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Parameter Estimation of Biological Phenomena: An Unscented Kalman Filter Approach

IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Speeding-up the learning of saccade control

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Non-recursive estimation using a batch filter based on particle filtering

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Combined cubature Kalman and smooth variable structure filtering: A robust nonlinear estimation strategy

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Hybrid fault diagnosis of nonlinear systems using neural parameter estimators

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Abrupt motion tracking using a visual saliency embedded particle filter

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Neural inverse optimal control applied to type 1 diabetes mellitus patients

Analog Integrated Circuits and Signal Processing
Adaptive evolutionary clustering

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Adaptive fuzzy system to forecast financial time series volatility

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A neuro-fuzzy approach in the classification of students' academic performance

Computational Intelligence and Neuroscience

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Abstract

From the Publisher:Kalman filtering is a well-established topic in the field of control and signal processing and represents by far the most refined method for the design of neural networks. This book takes a nontraditional nonlinear approach and reflects the fact that most practical applications are nonlinear. The book deals with important applications in such fields as control, financial forecasting, and idle speed control.