Using and designing massively parallel computers for artificial neural networks
Journal of Parallel and Distributed Computing - Special issue on neural computing on massively parallel processing
Hierarchical mixtures of experts and the EM algorithm
Neural Computation
Pulsed neural networks
The implementation of fuzzy systems, neural networks and fuzzy neural networks using
Information Sciences: an International Journal
Spike-Timing Dependent Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites
ICANN '02 Proceedings of the International Conference on Artificial Neural Networks
Hardware Requirements for Spike-Processing Neural Networks
IWANN '96 Proceedings of the International Workshop on Artificial Neural Networks: From Natural to Artificial Neural Computation
Autonomous Vehicle Guidance Using Analog VLSI Neuromorphic Sensors
ICANN '97 Proceedings of the 7th International Conference on Artificial Neural Networks
A Re-evaluation of the Practicality of Floating-Point Operations on FPGAs
FCCM '98 Proceedings of the IEEE Symposium on FPGAs for Custom Computing Machines
A SIMD/Dataflow Architecture for a Neurocomputer for Spike-Processing Neural Networks (NESPINN)
MICRONEURO '96 Proceedings of the 5th International Conference on Microelectronics for Neural Networks and Fuzzy Systems
ParSPIKE A Parallel DSP-Accelerator for Dynamic Simulation of Large Spiking Neural Networks
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
Simulation of a Digital Neuro-Chip for Spiking Neural Networks
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4 - Volume 4
Hardware spiking neural network with run-time reconfigurable connectivity in
EH '03 Proceedings of the 2003 NASA/DoD Conference on Evolvable Hardware
Intrinsic and extrinsic implementation of a bio-inspired hardware system
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Bio-inspired systems (BIS)
A neural simulation system based on biologically realistic electronic neurons
Information Sciences—Informatics and Computer Science: An International Journal - Special issue: Bio-inspired systems (BIS)
A Handel-C Implementation of the Back-Propagation Algorithm on Field Programmable Gate Arrays
RECONFIG '05 Proceedings of the 2005 International Conference on Reconfigurable Computing and FPGAs (ReConFig'05) on Reconfigurable Computing and FPGAs
Advances in Design and Application of Spiking Neural Networks
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Fuzzy-neural computation and robotics
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
IWANN '03 Proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks: Part II: Artificial Neural Nets Problem Solving Methods
A functional spiking neuron hardware oriented model
IWANN'03 Proceedings of the Artificial and natural neural networks 7th international conference on Computational methods in neural modeling - Volume 1
Comparative investigation into classical and spiking neuron implementations on FPGAs
ICANN'05 Proceedings of the 15th international conference on Artificial Neural Networks: biological Inspirations - Volume Part I
A silicon synapse based on a charge transfer device for spiking neural network application
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part III
Adaptive co-ordinate transformation based on a spike timing-dependent plasticity learning paradigm
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part I
A novel approach for the implementation of large scale spiking neural networks on FPGA hardware
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
Simple model of spiking neurons
IEEE Transactions on Neural Networks
Which model to use for cortical spiking neurons?
IEEE Transactions on Neural Networks
Real-time computing platform for spiking neurons (RT-spike)
IEEE Transactions on Neural Networks
EMBRACE: emulating biologically-inspired architectures on hardware
NN'08 Proceedings of the 9th WSEAS International Conference on Neural Networks
A Hardware Accelerated Simulation Environment for Spiking Neural Networks
ARC '09 Proceedings of the 5th International Workshop on Reconfigurable Computing: Architectures, Tools and Applications
International Journal of Reconfigurable Computing - Selected papers from ReCoSoc08
Connection-centric network for spiking neural networks
NOCS '09 Proceedings of the 2009 3rd ACM/IEEE International Symposium on Networks-on-Chip
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Optimal connectivity in hardware-targetted MLP networks
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Scalable event-driven native parallel processing: the SpiNNaker neuromimetic system
Proceedings of the 7th ACM international conference on Computing frontiers
ICES'10 Proceedings of the 9th international conference on Evolvable systems: from biology to hardware
ACM SIGARCH Computer Architecture News
Implementation of a field programmable gate array for wireless control of a lab-on-a-robot
Analog Integrated Circuits and Signal Processing
A hierachical configuration system for a massively parallel neural hardware platform
Proceedings of the 9th conference on Computing Frontiers
A large-scale spiking neural network accelerator for FPGA systems
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
A communication infrastructure for emulating large-scale neural networks models
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
Modular Neural Tile Architecture for Compact Embedded Hardware Spiking Neural Network
Neural Processing Letters
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The last 50 years has witnessed considerable research in the area of neural networks resulting in a range of architectures, learning algorithms and demonstrative applications. A more recent research trend has focused on the biological plausibility of such networks as a closer abstraction to real neurons may offer improved performance in an adaptable, real-time environment. This poses considerable challenges for engineers particularly in terms of the requirement to realise a low-cost embedded solution. Programmable hardware has been widely recognised as an ideal platform for the adaptable requirements of neural networks and there has been considerable research reported in the literature. This paper aims to review this body of research to identify the key lessons learned and, in particular, to identify the remaining challenges for large-scale implementations of spiking neural networks on FPGAs.