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ISTCS
1993
Springer
13 years 11 months ago
Analog Computation Via Neural Networks
We pursue a particular approach to analog computation, based on dynamical systems of the type used in neural networks research. Our systems have a xed structure, invariant in time...
Hava T. Siegelmann, Eduardo D. Sontag
IJCNN
2000
IEEE
14 years 17 hour ago
A 2D Neuromorphic VLSI Architecture for Modeling Selective Attention
Selectiveattentionis a mechanismsused to sequentiallyselectthe spatiallocationsof salientregionsin the sensor’sfieldof view. This mechanism overcomesthe problem of flooding limi...
Giacomo Indiveri
GECCO
2003
Springer
158views Optimization» more  GECCO 2003»
14 years 25 days ago
Active Control of Thermoacoustic Instability in a Model Combustor with Neuromorphic Evolvable Hardware
Continuous Time Recurrent Neural Networks (CTRNNs) have previously been proposed as an enabling paradigm for evolving analog electrical circuits to serve as controllers for physica...
John C. Gallagher, Saranyan Vigraham
CSREAESA
2004
13 years 9 months ago
CMOS Implementation of Phase-Encoded Complex-Valued Artificial Neural Networks
- The model of a simple perceptron using phase-encoded inputs and complex-valued weights is presented. Multilayer two-input and three-input complex-valued neurons (CVNs) are implem...
Howard E. Michel, David Rancour, Sushanth Iringent...
ESANN
2006
13 years 9 months ago
Parallel hardware implementation of a broad class of spiking neurons using serial arithmetic
Abstract. Current digital, directly mapped implementations of spiking neural networks use serial processing and parallel arithmetic. On a standard CPU, this might be the good choic...
Benjamin Schrauwen, Jan M. Van Campenhout