title: High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.
abstract: Spiking neural networks (SNN) are the last neural network generation that try to mimic the real behavior of biological neurons. Although most research in this area is done through software applications, it is in hardware implementations in which the intrinsic parallelism of these computing systems are more efficiently exploited. Liquid state machines (LSM) have arisen as a strategic technique to implement recurrent designs of SNN with a simple learning methodology. In this work, we show a new low-cost methodology to implement high-density LSM by using Boolean gates. The proposed method is based on the use of probabilistic computing concepts to reduce hardware requirements, thus considerably increasing the neuron count per chip. The result is a highly functional system that is applied to high-speed time series forecasting.
authors.affiliation: 1 Electronics Engineering Group, Physics Department, Universitat de les Illes Balears, Mateu Orfila Building, Cra. Valldemossa km. 7.5, Palma de Mallorca, Balears 07122, Spain.
authors.forename: Josep L
authors.initials: JL
authors.lastname: Rosselló
authors.affiliation: 1 Electronics Engineering Group, Physics Department, Universitat de les Illes Balears, Mateu Orfila Building, Cra. Valldemossa km. 7.5, Palma de Mallorca, Balears 07122, Spain.
authors.forename: Miquel L
authors.initials: ML
authors.lastname: Alomar
authors.affiliation: 1 Electronics Engineering Group, Physics Department, Universitat de les Illes Balears, Mateu Orfila Building, Cra. Valldemossa km. 7.5, Palma de Mallorca, Balears 07122, Spain.
authors.forename: Antoni
authors.initials: A
authors.lastname: Morro
authors.affiliation: 1 Electronics Engineering Group, Physics Department, Universitat de les Illes Balears, Mateu Orfila Building, Cra. Valldemossa km. 7.5, Palma de Mallorca, Balears 07122, Spain.
authors.forename: Antoni
authors.initials: A
authors.lastname: Oliver
authors.affiliation: 1 Electronics Engineering Group, Physics Department, Universitat de les Illes Balears, Mateu Orfila Building, Cra. Valldemossa km. 7.5, Palma de Mallorca, Balears 07122, Spain.
authors.forename: Vincent
authors.initials: V
authors.lastname: Canals
mesh_terms: D003198:Computer Simulation; D003201:Computers; D000069550:Machine Learning; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics; D011336:Probability; D013997:Time Factors
keywords: Spiking neural Networks; liquid State Machines; probabilistic computing; time series forecasting