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Network Software System Lab Department of Electrical Engineering, Technion

R andom N eural N etworks for C ognitive R adio M odeling. R. C. A recurrent neural network model inspired by the spiking behavior of biological neuronal networks Neurons in the RNN interact by probabilistically exchanging excitatory and inhibitory spiking signals

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Network Software System Lab Department of Electrical Engineering, Technion

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  1. Random Neural Networks for Cognitive Radio Modeling R C • A recurrent neural network model inspired by the spiking behavior of biological neuronal networks • Neurons in the RNN interact by probabilistically exchanging excitatory and inhibitory spiking signals • Model can be described by analytical equations, has low complexity and has many possible uses in engineering • In this Project we examined Random Neural Networks possible use in Radio Cognitive Modeling • Created an Environment allowing us to model spectral networks with variable parameters and measure their performance • Simulations indicates high performance with very low channel estimation error N R M N Network Software System Lab Department of Electrical Engineering, Technion Oz Itzhaki Jonathan Nafta Supervisor: Boris Oklander

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