Background: To evaluate the effect of the weighting of input imaging combo and ADC threshold on the performance of the U-Net and to find an optimized input imaging combo and ADC threshold in segmenting acute ischemic ...
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Continuous-variable (CV) teleportation is a fundamental protocol in quantum information science. A number of experiments have been designed to simulate ideal teleportation under realistic conditions. In this paper, we...
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Continuous-variable (CV) teleportation is a fundamental protocol in quantum information science. A number of experiments have been designed to simulate ideal teleportation under realistic conditions. In this paper, we detail an analytical approach for determining optimal input states for quantifying the performance of CV unidirectional and bidirectional teleportation. The metric that we consider for quantifying performance is the energy-constrained channel fidelity between ideal teleportation and its experimental implementation, and along with this, our focus is on determining optimal input states for distinguishing the ideal process from the experimental one. We prove that, under certain energy constraints, the optimal input state in unidirectional as well as bidirectional teleportation is a finite entangled superposition of twin-Fock states saturating the energy constraint. Moreover, we also prove that, under the same constraints, the optimal states are unique; that is, there is no other optimal finite entangled superposition of twin-Fock states.
Electrolyte-insulator-semiconductor (EIS)-based sensors are a novel class of electronic chips designed for biochemical sensing that offer a direct electronic readout, making them part of a new generation of sensing te...
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The importance of proper data normalization for deep neural networks is well known. However, in continuous-time state-space model estimation, it has been observed that improper normalization of either the hidden state...
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Differential passivity of a nonlinear system has been introduced as passivity of its variational system. Applying standard passivity-based control techniques to differentially passive systems leads to controllers for ...
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ISBN:
(数字)9798350316339
ISBN:
(纸本)9798350316346
Differential passivity of a nonlinear system has been introduced as passivity of its variational system. Applying standard passivity-based control techniques to differentially passive systems leads to controllers for the corresponding variational systems. However, it is challenging to construct controllers for the original nonlinear systems if the differential passive outputs are non-exact differential one-forms. In this letter, our objective is to provide a systematic procedure to address this issue when differential passive outputs are integrable, i.e., when non-exact differential passive outputs can be made exact by multiplying them by suitable integrating factors. In particular, under suitable detectability assumptions, we propose one static and two dynamic state feedback stabilizing controllers, where each dynamic controller has a form of input-and output-shaping, respectively. We illustrate their effectiveness by stabilization of counter-current heat exchangers.
The integration of brain-machine interface and exoskeleton robot has been widespread application in gait correction, walking assistance, and numerous other scenarios. To effectively extract the electroencephalogram (E...
The integration of brain-machine interface and exoskeleton robot has been widespread application in gait correction, walking assistance, and numerous other scenarios. To effectively extract the electroencephalogram (EEG) signal features of motor imagery while wearing an exoskeleton, this study proposes a frequency band pre-determination method based on power spectral density (PSD) that enables common spatial patterns (CSP) to extract features from the frequency band with the highest energy in the EEG. The signal power spectral density of all channels is obtained at or near the average frequency of the maximum short interval frequency component energy. A second round of filtering is performed on the data, and the signal components are used as input for the subsequent feature extraction step. The CSP method extracts features from the spatial domain signal and generates feature maps. Finally, Support Vector Machines (SVM) are utilized to classify the EEG signals. Based on the pre-set gait of the exoskeleton robot and the motor imagery paradigm, feature extraction and classification of motor imagery EEG data during exoskeleton use were conducted, with an average accuracy rate of 77%. The experimental results demonstrate the effectiveness of this method in extracting the motor imagery EEG features during exoskeleton use.
Quantum communication relies on the existence of high quality quantum channels to exchange information. In practice, however, all communication links are affected by noise from the environment. Here we investigate the...
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PDMATLAB2D is a meshfree peridynamics implementation in MATLAB suitable for simulation of two-dimensional fracture problems. The purpose of this code is twofold. First, it provides an entry-level peridynamics computat...
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Electro-optic phase modulators are commonly used for polarization and phase encoding in quantum key distribution. Here, a novel state preparation flaw which arises during high speed electro-optic phase modulation is i...
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ISBN:
(纸本)9781957171258
Electro-optic phase modulators are commonly used for polarization and phase encoding in quantum key distribution. Here, a novel state preparation flaw which arises during high speed electro-optic phase modulation is identified and characterized. The impact of this state preparation flaw on the secure key rate is quantified.
While monotone operator theory is often studied on Hilbert spaces, many interesting problems in machine learning and optimization arise naturally in finite-dimensional vector spaces endowed with non-Euclidean norms, s...
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