Physics – Data Analysis – Statistics and Probability
Scientific paper
2009-02-15
Physics
Data Analysis, Statistics and Probability
23 pages, 2 figures, submitetd to IEEE Transactions on Neural Networks in December 2008
Scientific paper
In the first part in [12], we present and analyse a Sigmoid-based "Signal-to-Interference Ratio, (SIR)" balancing dynamic network, called Sgm"SIR"NN, which exhibits similar properties as traditional Hopfield NN does, in continuous time. In this second part, we present the corresponding network in discrete time: We show that in the proposed discrete-time network, called D-Sgm"SIR"NN, the defined error vector approaches to zero in a finite step in both synchronous and asynchronous work modes. Our investigations show that i) Establishing an analogy to the distributed (sigmoid) power control algorithm in [10] and [11] if the defined fictitious "SIR" is equal to 1 at the converged eqiulibrium point, then it is one of the prototype vectors. ii) The D-Sgm"SIR"NN exhibits similar features as discrete-time Hopfield NN does. iii) Establishing an analogy to the traditional 1-bit fixed-step power control algorithm, the corresponding "1-bit" network, called Sign"SIR"NN network, is also presented.
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