29 citations · 42 across the 9 of their papers we have counts for
10 papers
CeMux: Maximizing the Accuracy of Stochastic Mux Adders and an Application to Filter Design
Timothy J. Baker, John P. Hayes
Stochastic computing (SC) is a low-cost computational paradigm that has promising applications in digital filter design, image processing and neural networks. Fundamental to these…
Energy-Efficient Hybrid Stochastic-Binary Neural Networks for Near-Sensor Computing
Vincent T. Lee, Armin Alaghi, John P. Hayes +2
Recent advances in neural networks (NNs) exhibit unprecedented success at transforming large, unstructured data streams into compact higher-level semantic information for tasks suc…
Checking Equivalence of Quantum Circuits and States
George F. Viamontes, Igor L. Markov, John P. Hayes
Quantum computing promises exponential speed-ups for important simulation and optimization problems. It also poses new CAD problems that are similar to, but more challenging, than…
Is Quantum Search Practical?
George F. Viamontes, Igor L. Markov, John P. Hayes
Quantum algorithms and circuits can, in principle, outperform the best non-quantum (classical) techniques for some hard computational problems. However, this does not necessarily l…
Fault Testing for Reversible Circuits
Ketan N. Patel, John P. Hayes, Igor L. Markov
Applications of reversible circuits can be found in the fields of low-power computation, cryptography, communications, digital signal processing, and the emerging field of quantum…
Graph-based simulation of quantum computation in the density matrix representation
George F. Viamontes, Igor L. Markov, John P. Hayes
Quantum-mechanical phenomena are playing an increasing role in information processing, as transistor sizes approach the nanometer level, and quantum circuits and data encoding meth…