A significant bottleneck to the use of associative memories in real-time systems is the amount of data that requires processing. The aim of this paper is to present the work that produced a dedicated hardware design that will run a major part of the ADAM algorithm. The work selected a portion of the algorithm to implement using FPGA technology. The Sum And Threshold (SAT) processor has been simulated and shown to process data fifty times faster than the current DSP based system that uses a dedicated peripheral processor. The paper includes analysis of the speed characteristics of the SAT processor, along with an analysis of the design. The design analysis highlights a bottleneck in the design to which a solution is proposed for future work....
Living creatures pose amazing ability to learn and adapt, therefore researchers are trying to apply ...
Analog VLSI circuits are being used successfully to implement Artificial Neural Networks (ANNs). The...
Re-awaking in the 1980s from a rather chequered history Artificial Neural Networks (ANNs) have susta...
Artificial Neural Network (ANN) is very powerful to deal with signal processing, computer vision and...
Rückert U, Funke A, Pintaske C. Acceleratorboard for Neural Associative Memories. Neurocomputing. 19...
The design of an auto-associative memory based on a spiking neural network is described. Delays rath...
Rückert U. An Associative Memory with Neural Architecture and its VLSI Implementation. In: Milutinov...
Rückert U. VLSI Implementation of an Associative Memory Based on Distributed Storage of Information....
The associative memory (AM) chip is ASIC device specifically designed to perform ``pattern matching'...
The associative memory (AM) system is a computing device made of hundreds of AM ASICs chips designed...
Artificial neural networks are now being used for many applications in the technology world. Signal ...
Rückert U, Rüping S, Naroska E. Parallel Implementation of Neural Associative Memories on RISC Proce...
This thesis presents a feasibility analysis for hardware acceleration of the pattern recognition alg...
. The implementation of larger digital neural networks has not been possible due to the real-estate ...
Multi-dimensional classification tasks by neural methods are interesting for their performances and ...
Living creatures pose amazing ability to learn and adapt, therefore researchers are trying to apply ...
Analog VLSI circuits are being used successfully to implement Artificial Neural Networks (ANNs). The...
Re-awaking in the 1980s from a rather chequered history Artificial Neural Networks (ANNs) have susta...
Artificial Neural Network (ANN) is very powerful to deal with signal processing, computer vision and...
Rückert U, Funke A, Pintaske C. Acceleratorboard for Neural Associative Memories. Neurocomputing. 19...
The design of an auto-associative memory based on a spiking neural network is described. Delays rath...
Rückert U. An Associative Memory with Neural Architecture and its VLSI Implementation. In: Milutinov...
Rückert U. VLSI Implementation of an Associative Memory Based on Distributed Storage of Information....
The associative memory (AM) chip is ASIC device specifically designed to perform ``pattern matching'...
The associative memory (AM) system is a computing device made of hundreds of AM ASICs chips designed...
Artificial neural networks are now being used for many applications in the technology world. Signal ...
Rückert U, Rüping S, Naroska E. Parallel Implementation of Neural Associative Memories on RISC Proce...
This thesis presents a feasibility analysis for hardware acceleration of the pattern recognition alg...
. The implementation of larger digital neural networks has not been possible due to the real-estate ...
Multi-dimensional classification tasks by neural methods are interesting for their performances and ...
Living creatures pose amazing ability to learn and adapt, therefore researchers are trying to apply ...
Analog VLSI circuits are being used successfully to implement Artificial Neural Networks (ANNs). The...
Re-awaking in the 1980s from a rather chequered history Artificial Neural Networks (ANNs) have susta...