297 results on '"Principe, José C."'
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2. Cubature Kalman Filtering Under Information Theoretic Criteria
3. Kalman Filtering
4. Unscented Kalman Filter Under Information Theoretic Criteria
5. Kalman Filtering Under Information Theoretic Criteria
6. Extended Kalman Filtering Under Information Theoretic Criteria
7. Information Theoretic Criteria
8. Introduction
9. EEG Models and Analysis
10. Message transmission in the presence of noise. Second asymptotic theorem and its various formulations
11. First asymptotic theorem and related results
12. Channel capacity. Important particular cases of channels
13. Definition of the value of information
14. Information in the presence of noise. Shannon’s amount of information
15. Encoding of discrete information in the absence of noise and penalties
16. Computation of entropy for special cases. Entropy of stochastic processes
17. Encoding in the presence of penalties. First variational problem
18. Definition of information and entropy in the absence of noise
19. Asymptotic results about the value of information. Third asymptotic theorem
20. Information theory and the second law of thermodynamics
21. Value of Shannon’s information for the most important Bayesian systems
22. Trading Utility and Uncertainty: Applying the Value of Information to Resolve the Exploration–Exploitation Dilemma in Reinforcement Learning
23. The Generalized Sleep Spindles Detector: A Generative Model Approach on Single-Channel EEGs
24. Correction to: Theory of Information and its Value
25. Cognitive Workload Discrimination in Flight Simulation Task Using a Generalized Measure of Association
26. Theoretical Methods in Machine Learning
27. Information Theory, Machine Learning, and Reproducing Kernel Hilbert Spaces
28. Online Nonlinear Granger Causality Detection by Quantized Kernel Least Mean Square
29. Nonlinear Adaptive Filtering in Kernel Spaces
30. BMI/BCI Modeling and Signal Processing
31. Neural Decoding Using Generative BMI Models
32. BMI Systems
33. Adaptive Algorithms for Point Processes
34. Regularization Techniques for BMI Models
35. Introduction to Neural Interfaces
36. Foundations of Neuronal Representations
37. Input–Output BMI Models
38. Kernel Principal Components Are Maximum Entropy Projections
39. Decoding Algorithms for Brain–Machine Interfaces
40. Correntropy in Data Classification
41. Optimization in Reproducing Kernel Hilbert Spaces of Spike Trains
42. Linear Projection Method Based on Information Theoretic Learning
43. Development of Symbiotic Brain-Machine Interfaces Using a Neurophysiology Cyberworkstation
44. Towards Real-Time Distributed Signal Modeling for Brain-Machine Interfaces
45. Computational Neural Networks
46. Optimizing the Cauchy-Schwarz PDF Distance for Information Theoretic, Non-parametric Clustering
47. Information Theoretic Organization Principles for Autonomous Multiple-Agents
48. Information Force Clustering Using Directed Trees
49. Dataflow Learning in Coupled Lattices: An Application to Artificial Neural Networks
50. Local Modeling Using Self-Organizing Maps and Single Layer Neural Networks
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