The application would effectively avoid the problems of time delay and low accuracy which result from the manual analysis. In order to eliminate the redundant information stored in variables, principal component analysis (PCA) is adopted to reduce the number of input variables of ELM-QNN. The ...
We demonstrate the feasibility of framing a classically learned deep neural network as an energy based model that can be processed on a one-step quantum annealer in order to exploit fast sampling times. We propose approaches to overcome two hurdles for high resolution image classification on a qua...
aSTM capacity from single-qubit observables depending on the delayτobtained with the different protocols andNmeas = 1.5 ⋅ 106measurements (symbols). The ideal capacities (Nmeas → ∞), are represented with a solid line in the corresponding color; the unperturbed situation is in...
(92) and (92), i.e., the delay depends on the cardinality of the coincidence set and the incoming entanglement rate (This relation also can be derived from Little’s law;
|H⟩|H〉 (|V⟩|V〉) and reflects those with |V⟩|V〉 (|H⟩|H〉); a half-wave plate H flips the polarization of photons passing it and performs the conversion |V⟩↔|H⟩|V〉↔|H〉; τ is a time delay operator that introduces an optical delay of τ∆....
Delay-dependent global asymptotic stability criteria for a class ofcellular neural networks; 一类细胞神经网络的时滞相关全局稳定性判据 更多例句>> 4) Cellular Neural Network(CNN) 细胞神经网络 1. The stability of the network and the parameter choice are the key problems when Cellular Neural Network(CN...
In the search for optimal control sequences, where the success can only be judged with some time-delay, reinforcement learning is the method of choice. We have explored how a neural-network based agent can be trained to generate optimal control sequences for quantum feedback, where the agent...
Using a slightly simplified version of the integrate and fire model of a neural network with delay, I study the stability of the phase-locked state depende... H Haken - 《Physics of Condensed Matter》 被引量: 68发表: 2000年 Loss of phase-locking in non-weakly coupled inhibitory networks ...
Neural Network Fig. 5: A Quantum Spiking Neural Network structure, processing an image converted to brightness values and then to spike trains to pass through the network. Full size image $$\frac{\partial {\mathcal{L}}}{\partial W}=\sum _{t}\frac{\partial {\mathcal{L}}[t]}{\parti...
Figure 2. Network delay of classical exact algorithm, quantum annealing, quantum annealing after gap expansion, and simulated annealing are plotted versus time slot for two randomly generated networks. The left one is a simpler case with 15 nodes and 31 edges where quantum annealing reaches ...