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The dense interconnections that characterize neural networks are most readily implemented using optical signal processing. Optoelectronic 'neurons' fabricated from semiconducting materials can be connected by holographic images recorded in photorefractive ...
In order to assist the field of neural networks in its maturing, a formalization and a solid foundation are essential. Additionally, to permit the introduction of formal proofs, it is essential to have an all encompassing formal mathematical definition of ...
The operating point of a power system can be defined as a vector whose components are active and reactive power measurements. If the security criterion is prevention of line overloads, the boundaries of the secure domain of the state space are given by the ...
The applicability of neural networks to a typical biochem. engineering problem was investigated. The data treatment required for a novel technique for measuring the mean bubble size and the sp. interfacial area in aerobic bioreactors was chosen as an appro ...
The applicability of neural networks to a typical biochemical engineering problem was investigated. The data treatment required for a novel technique for measuring the mean bubble size and the specific interfacial area in aerobic bioreactors was chosen as ...
Neural networks are highly effective tools for pose estimation. However, robustness to outof-domain data remains a challenge, especially for small training sets that are common for real world applications. Here, we probe the generalization ability with thr ...
We propose a recurrent neural-network for real-time reconstruction of acoustic camera spherical maps. The network, dubbed DeepWave, is both physically and algorithmically motivated: its recurrent architecture mimics iterative solvers from convex optimisati ...
