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TNN
2008

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Complex ICA by Negentropy Maximization

13 years 4 months ago

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In this paper, we use complex analytic functions to achieve independent component analysis (ICA) by maximization of non-Gaussianity and introduce the complex maximization of nonGau...

Mike Novey, Tülay Adali

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Id	Views	Title	Status

1	187	Complex ICA by Negentropy Maximization	claim
2	182	Large-Scale Maximum Margin Discriminant Analysis Using Core Vector Machines	claim
3	181	Optimized Approximation Algorithm in Neural Networks Without Overfitting	claim
4	178	IMORL: Incremental Multiple-Object Recognition and Localization	claim
5	177	Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model	claim
6	171	Adaptive Dynamic Inversion via Time-Scale Separation	claim
7	152	Distributed Parallel Support Vector Machines in Strongly Connected Networks	claim
8	143	Blur Identification by Multilayer Neural Network Based on Multivalued Neurons	claim
9	142	Multiclass Posterior Probability Support Vector Machines	claim
10	141	MPCA: Multilinear Principal Component Analysis of Tensor Objects	claim
11	138	A Fast and Scalable Recurrent Neural Network Based on Stochastic Meta Descent	claim
12	133	A General Wrapper Approach to Selection of Class-Dependent Features	claim
13	132	Just-in-Time Adaptive Classifiers - Part I: Detecting Nonstationary Changes	claim
14	129	Data Visualization and Dimensionality Reduction Using Kernel Maps With a Reference Point	claim
15	128	A Hybrid Technique for Blind Separation of Non-Gaussian and Time-Correlated Sources Using a Multicomponent Approach	claim
16	128	Nonnegative Matrix Factorization in Polynomial Feature Space	claim
17	124	Just-in-Time Adaptive Classifiers - Part II: Designing the Classifier	claim
18	122	Two-Microphone Separation of Speech Mixtures	claim
19	119	Selecting Useful Groups of Features in a Connectionist Framework	claim
20	114	Relevance-Based Feature Extraction for Hyperspectral Images	claim
21	112	Matrix-Variate Factor Analysis and Its Applications	claim
22	112	Multilayer Perceptrons: Approximation Order and Necessary Number of Hidden Units	claim
23	108	A Novel Recurrent Neural Network for Solving Nonlinear Optimization Problems With Inequality Constraints	claim
24	106	Unsupervised Segmentation With Dynamical Units	claim
25	106	Stability and Hopf Bifurcation of a General Delayed Recurrent Neural Network	claim
26	105	Incremental Learning of Chunk Data for Online Pattern Classification Systems	claim
27	105	Generalized Linear Discriminant Analysis: A Unified Framework and Efficient Model Selection	claim
28	102	Robust Synchronization of an Array of Coupled Stochastic Discrete-Time Delayed Neural Networks	claim
29	102	A Class of Complex ICA Algorithms Based on the Kurtosis Cost Function	claim
30	101	Comments on "The Extreme Learning Machine"	claim
31	100	Global Asymptotic Stability of Recurrent Neural Networks With Multiple Time-Varying Delays	claim
32	100	Global Exponential Stability of Bidirectional Associative Memory Neural Networks With Time Delays	claim
33	98	Symmetric RBF Classifier for Nonlinear Detection in Multiple-Antenna-Aided Systems	claim
34	97	Training Hard-Margin Support Vector Machines Using Greedy Stagewise Algorithm	claim
35	96	Global Convergence and Limit Cycle Behavior of Weights of Perceptron	claim
36	95	A Constrained Optimization Approach to Preserving Prior Knowledge During Incremental Training	claim
37	95	Minimizing the Effect of Process Mismatch in a Neuromorphic System Using Spike-Timing-Dependent Adaptation	claim
38	94	Individual Stable Space: An Approach to Face Recognition Under Uncontrolled Conditions	claim
39	93	Towards the Optimal Design of Numerical Experiments	claim
40	90	Distributed EM Algorithm for Gaussian Mixtures in Sensor Networks	claim
41	90	Shared Feature Extraction for Nearest Neighbor Face Recognition	claim
42	88	A New Approach to Knowledge-Based Design of Recurrent Neural Networks	claim
43	88	A Fault-Tolerant Regularizer for RBF Networks	claim
44	87	Stochastic Resonance in Continuous and Spiking Neuron Models With Levy Noise	claim
45	86	Trend Time-Series Modeling and Forecasting With Neural Networks	claim
46	85	Training Spiking Neuronal Networks With Applications in Engineering Tasks	claim
47	82	Deterministic Learning for Maximum-Likelihood Estimation Through Neural Networks	claim
48	81	Nonlinear Knowledge-Based Classification	claim
49	79	Performing Feature Selection With Multilayer Perceptrons	claim
50	78	Automatic Relevance Determination for Identifying Thalamic Regions Implicated in Schizophrenia	claim
51	76	Maxi-Min Margin Machine: Learning Large Margin Classifiers Locally and Globally	claim
52	74	Pattern Representation in Feature Extraction and Classifier Design: Matrix Versus Vector	claim
53	70	Robust Neural Network Tracking Controller Using Simultaneous Perturbation Stochastic Approximation	claim
54	67	A-Optimality Orthogonal Forward Regression Algorithm Using Branch and Bound	claim
55	67	Local Classifier Weighting by Quadratic Programming	claim
56	67	Simple Method for High-Performance Digit Recognition Based on Sparse Coding	claim
57	65	Local and Global Stability Analysis of an Unsupervised Competitive Neural Network	claim
58	57	Pattern Recognition	claim

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