Abstract:
This paper is concerned with the problem of recovering multiple source signals that are transmitted through a linear Multiple Input Multiple Output (MIMO) system, without...Show MoreMetadata
Abstract:
This paper is concerned with the problem of recovering multiple source signals that are transmitted through a linear Multiple Input Multiple Output (MIMO) system, without resorting to any prior knowledge. Source signals are assumed to be spatially independent and temporally i.i.d. non-Gaussian sequences. We present an unsupervised hybrid network (a linear feedback network with FIR synapses followed by a linear memoryless feedforward network) which is able to recover multiple source signals blindly. A simple criterion for multichannel blind deconvolution and an associated learning algorithm are presented. Extensive computer simulation results confirm the validity and high performance of the proposed method.
Published in: Journal of Communications and Networks ( Volume: 1, Issue: 1, March 1999)
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- IEEE Keywords
- Index Terms
- Signal Source ,
- Hybrid Network ,
- Blind Separation ,
- Multipath Environment ,
- Learning Algorithms ,
- Computer Simulations ,
- Additive Noise ,
- Singular Value Decomposition ,
- Independent Component Analysis ,
- Feed-forward Network ,
- Sensory Signals ,
- Decorrelation ,
- Linear Network ,
- Blind Source Separation ,
- Channel Impulse Response ,
- Mixture Of Signals ,
- Blind Deconvolution ,
- Neural Network ,
- Learning Rate ,
- Signal Processing ,
- Synaptic Weights ,
- Joint Probability Density Function ,
- Mixed Phase ,
- Multiple-input Single-output ,
- Result Of Theorem ,
- Kullback-Leibler ,
- Stage Of Network ,
- Marginal Density Function ,
- Delay Length ,
- Communication Signals
- Author Keywords
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Signal Source ,
- Hybrid Network ,
- Blind Separation ,
- Multipath Environment ,
- Learning Algorithms ,
- Computer Simulations ,
- Additive Noise ,
- Singular Value Decomposition ,
- Independent Component Analysis ,
- Feed-forward Network ,
- Sensory Signals ,
- Decorrelation ,
- Linear Network ,
- Blind Source Separation ,
- Channel Impulse Response ,
- Mixture Of Signals ,
- Blind Deconvolution ,
- Neural Network ,
- Learning Rate ,
- Signal Processing ,
- Synaptic Weights ,
- Joint Probability Density Function ,
- Mixed Phase ,
- Multiple-input Single-output ,
- Result Of Theorem ,
- Kullback-Leibler ,
- Stage Of Network ,
- Marginal Density Function ,
- Delay Length ,
- Communication Signals
- Author Keywords