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Titlebook: Unconventional Computation; 6th International Co Selim G. Akl,Cristian S. Calude,H. Todd Wareham Conference proceedings 2007 Springer-Verla

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Unconventional Models of Computation Through Non-standard Logic Circuitsogics (namely, to all truth-functional propositional logics and to some non-truth-functional logics). Such generalization allows us to define models of computation based on non-standard logics in a natural way by using ‘hidden variables’ in the constitution of the model. . for the paraconsistent log
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Unconventional “Stateless” Turing–Like Machines way they can “remember” anything is by writing on their tapes. Stateless TMs have limited computing power: They cannot compute all computable functions. However, this handicap of a stateless TM can be overcome if we modify the TM a little by adding an extra feature. We propose a modified Turing–lik
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Learning Vector Quantization Network for PAPR Reduction in Orthogonal Frequency Division Multiplexine when the signal has to be amplified with a non linear high power amplifier (HPA). This paper proposes an efficient PAPR reduction technique by taking the benefit of the classification capability of Learning Vector Quantization (LVQ) network. The symbols are classified in different classes and are
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Binary Ant Colony Algorithm for Symbol Detection in a Spatial Multiplexing Systemtion (ACO) based Multi-Input Multi-Output (MIMO) detection algorithm gives near-optimal Bit Error Rate (BER) performance with reduced computational complexity. The simulation results suggest that the reported unconventional detector gives an acceptable performance complexity trade-off in comparison
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