The Experts below are selected from a list of 3144 Experts worldwide ranked by ideXlab platform
J. B. Wang - One of the best experts on this subject based on the ideXlab platform.
-
Quantum Fourier transform in Computational Basis
Quantum Information Processing, 2017Co-Authors: S. S. Zhou, T. Loke, J. A. Izaac, J. B. WangAbstract:The quantum Fourier transform, with exponential speed-up compared to the classical fast Fourier transform, has played an important role in quantum computation as a vital part of many quantum algorithms (most prominently, Shor’s factoring algorithm). However, situations arise where it is not sufficient to encode the Fourier coefficients within the quantum amplitudes, for example in the implementation of control operations that depend on Fourier coefficients. In this paper, we detail a new quantum scheme to encode Fourier coefficients in the Computational Basis, with fidelity $$1 - \delta $$ 1 - δ and digit accuracy $$\epsilon $$ ϵ for each Fourier coefficient. Its time complexity depends polynomially on $$\log (N)$$ log ( N ) , where N is the problem size, and linearly on $$1/\delta $$ 1 / δ and $$1/\epsilon $$ 1 / ϵ . We also discuss an application of potential practical importance, namely the simulation of circulant Hamiltonians.
Feng Rong - One of the best experts on this subject based on the ideXlab platform.
-
sensorimotor integration in speech processing Computational Basis and neural organization
Neuron, 2011Co-Authors: Gregory Hickok, John Houde, Feng RongAbstract:Sensorimotor integration is an active domain of speech research and is characterized by two main ideas, that the auditory system is critically involved in speech production and that the motor system is critically involved in speech perception . Despite the complementarity of these ideas, there is little crosstalk between these literatures. We propose an integrative model of the speech-related "dorsal stream" in which sensorimotor interaction primarily supports speech production, in the form of a state feedback control architecture. A critical component of this control system is forward sensory prediction, which affords a natural mechanism for limited motor influence on perception, as recent perceptual research has suggested. Evidence shows that this influence is modulatory but not necessary for speech perception. The neuroanatomy of the proposed circuit is discussed as well as some probable clinical correlates including conduction aphasia, stuttering, and aspects of schizophrenia.
-
Sensorimotor Integration in Speech Processing: Computational Basis and Neural Organization
Neuron, 2011Co-Authors: Gregory Hickok, John Houde, Feng RongAbstract:Sensorimotor integration is an active domain of speech research and is characterized by two main ideas, that the auditory system is critically involved in speech production and that the motor system is critically involved in speech perception. Despite the complementarity of these ideas, there is little crosstalk between these literatures. We propose an integrative model of the speech-related " dorsal stream" in which sensorimotor interaction primarily supports speech production, in the form of a state feedback control architecture. A critical component of this control system is forward sensory prediction, which affords a natural mechanism for limited motor influence on perception, as recent perceptual research has suggested. Evidence shows that this influence is modulatory but not necessary for speech perception. The neuroanatomy of the proposed circuit is discussed as well as some probable clinical correlates including conduction aphasia, stuttering, and aspects of schizophrenia. © 2011 Elsevier Inc.
S. S. Zhou - One of the best experts on this subject based on the ideXlab platform.
-
Quantum Fourier transform in Computational Basis
Quantum Information Processing, 2017Co-Authors: S. S. Zhou, T. Loke, J. A. Izaac, J. B. WangAbstract:The quantum Fourier transform, with exponential speed-up compared to the classical fast Fourier transform, has played an important role in quantum computation as a vital part of many quantum algorithms (most prominently, Shor’s factoring algorithm). However, situations arise where it is not sufficient to encode the Fourier coefficients within the quantum amplitudes, for example in the implementation of control operations that depend on Fourier coefficients. In this paper, we detail a new quantum scheme to encode Fourier coefficients in the Computational Basis, with fidelity $$1 - \delta $$ 1 - δ and digit accuracy $$\epsilon $$ ϵ for each Fourier coefficient. Its time complexity depends polynomially on $$\log (N)$$ log ( N ) , where N is the problem size, and linearly on $$1/\delta $$ 1 / δ and $$1/\epsilon $$ 1 / ϵ . We also discuss an application of potential practical importance, namely the simulation of circulant Hamiltonians.
Peter Soliz - One of the best experts on this subject based on the ideXlab platform.
-
EMBC - Computational Basis for risk stratification of peripheral neuropathy from thermal imaging
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and, 2012Co-Authors: E. Simon Barriga, Viktor Chekh, Cesar Carranza, Mark R. Burge, Ana Edwards, Elizabeth Mcgrew, Gilberto Zamora, Peter SolizAbstract:The goal of this paper is to present a computer-based system for analyzing thermal images in the detection of preclinical stages of peripheral neuropathy (PN) or diabetic foot. Today, vibration perception threshold (VPT) and sensory tests with a monofilament are used as simple, noninvasive methods for identifying patients who have lost sensation in their feet. These tests are qualitative and are ineffective in stratifying risk for PN in a diabetic patient. In our system a cold stimulus applied to the foot causes a thermoregulatory and corresponding microcirculation response of the foot. A thermal video monitors the recovery of the microcirculation in the foot plantar. Thermal videos for 8 age-matched subjects were analyzed. Six sites were tracked and an average thermal emittance calculated. Characteristics of the recovery curve were extracted using coefficients from an exponential curve fitting process and compared among subjects. The magnitude of the recovery was significantly different for the two classes of subjects. Our system shows evidence of differences between both groups, which could lead to a quantitative test to screen and diagnose peripheral neuropathy.
-
Computational Basis for risk stratification of peripheral neuropathy from thermal imaging
2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2012Co-Authors: Simon E. Barriga, Viktor Chekh, Cesar Carranza, Mark R. Burge, Ana Edwards, Elizabeth Mcgrew, Gilberto Zamora, Peter SolizAbstract:The goal of this paper is to present a computer-based system for analyzing thermal images in the detection of preclinical stages of peripheral neuropathy (PN) or diabetic foot. Today, vibration perception threshold (VPT) and sensory tests with a monofilament are used as simple, noninvasive methods for identifying patients who have lost sensation in their feet. These tests are qualitative and are ineffective in stratifying risk for PN in a diabetic patient. In our system a cold stimulus applied to the foot causes a thermoregulatory and corresponding microcirculation response of the foot. A thermal video monitors the recovery of the microcirculation in the foot plantar. Thermal videos for 8 age-matched subjects were analyzed. Six sites were tracked and an average thermal emittance calculated. Characteristics of the recovery curve were extracted using coefficients from an exponential curve fitting process and compared among subjects. The magnitude of the recovery was significantly different for the two classes of subjects. Our system shows evidence of differences between both groups, which could lead to a quantitative test to screen and diagnose peripheral neuropathy.
Jiman Zhao - One of the best experts on this subject based on the ideXlab platform.
-
quantum qr decomposition in the Computational Basis
Quantum Information Processing, 2020Co-Authors: Hongbo Li, Jiman ZhaoAbstract:In this paper, we propose a quantum algorithm for approximating the QR decomposition of any $$N\times N$$ matrix with a running time $$O(\frac{1}{\epsilon ^2}$$ $$N^{2.5}\text {polylog}(N))$$ , where $$\epsilon $$ is the desired precision. This quantum algorithm provides a polynomial speedup over the best classical algorithm, which has a running time $$O(N^3)$$ . Our quantum algorithm utilizes the quantum computation in the Computational Basis (QCCB) and a setting of updatable quantum memory. We further present a systematic approach to applying the QCCB to simulate any quantum algorithm. By this approach, the simulation time does not exceed $$O(N^2\text {polylog}(N))$$ times the running time of the quantum algorithm originally designed with the amplitude encoding method, where N is the size of the problem.