Results 111 to 120 of about 5,938,476 (293)

An Adaptive Inhibitory WSe2 Transistor for Retinomorphic In‐Sensor Image Processing

open access: yesAdvanced Functional Materials, EarlyView.
Conventional retinomorphic devices typically require deliberate gate‐bias tuning for each illumination condition. In this paper, we demonstrate an adaptive inhibitory WSe2 transistor that uses photo‐induced regime shift between the subthreshold and accumulation modes to achieve decision‐free, intensity‐adaptive image processing within a single pixel ...
Juhwan Baek   +12 more
wiley   +1 more source

Application of a Modified Generalized Regression Neural Networks Algorithm in Economics and Finance [PDF]

open access: yes, 2011
In this paper we propose an alternative and modified Generalized Regression Neural Networks Autoregressive model (GRNN-AR) in S&P 500 and FTSE 100 index returns, as also in Gross domestic product growth rate of Italy, USA and UK. We compare the forecasts
Giovanis, Eleftherios
core  

Fiber‐Based Wearable Electronics as Adaptive Biointerfaces for Healthcare Applications

open access: yesAdvanced Functional Materials, EarlyView.
Fiber‐based wearable electronics have been extensively studied as adaptive healthcare biointerfaces. In this review, we classify and introduce fiber‐based systems according to biointerface design, conductive materials, transduction mechanisms, and healthcare applications, and provide a perspective on their translation toward reliable, continuous ...
Sangwoo Hong   +5 more
wiley   +1 more source

Analog Classification of Human Hand Gestures Exploiting Dendritic Integration With an Organic Artificial Soma

open access: yesAdvanced Functional Materials, EarlyView.
An organic neuromorphic architecture for the classification of human motor behavior is presented and validated. It performs somatic integration by linearly combining the activity from three muscles. An investigation of synaptic weights is presented and discussed in relationship with the classification performance.
Ilenia Sergi   +7 more
wiley   +1 more source

Pluggable multitask diffractive neural networks based on cascaded metasurfaces

open access: yesOpto-Electronic Advances
Optical neural networks have significant advantages in terms of power consumption, parallelism, and high computing speed, which has intrigued extensive attention in both academic and engineering communities.
Cong He   +10 more
doaj   +1 more source

Degradable, Skin‐Conformal Nanocomposite‐Based Bioelectronic Patches for High‐Fidelity Electrophysiology and Gesture‐Controlled Robotics

open access: yesAdvanced Functional Materials, EarlyView.
A degradable, skin‐conformal bioelectronic patch combines a starch‐dominated nanocomposite conductor with a gelatin substrate to enable sensitive strain sensing, high‐fidelity electrocardiography, electromyography, electrooculography, and machine‐learning‐assisted gesture control.
Ming Dong   +10 more
wiley   +1 more source

Multiplexed orbital angular momentum beams demultiplexing using hybrid optical-electronic convolutional neural network

open access: yesCommunications Physics
Advancements in optical communications have increasingly focused on leveraging spatial-structured beams such as orbital angular momentum (OAM) beams for high-capacity data transmission.
Jiachi Ye   +11 more
doaj   +1 more source

Nitrospinics: Nitride Materials for Spin‐Orbit and Orbital Torques From Memory to Artificial Intelligence

open access: yesAdvanced Functional Materials, EarlyView.
Further advances in applications can be anticipated through the development of unique and functional materials beyond conventional alloys. Nitrogen enables tailor‐made orbital textures in various transition‐metal hosts, paving the way for devices ranging from spintronics memory to artificial intelligence hardware.
Prabhat Kumar   +3 more
wiley   +1 more source

Compressing and expanding optical matrix-vector multipliers for enabling optical image encoder-decoders and generators

open access: yesLight: Science & Applications
Both compressing and expanding optical matrix-vector multipliers are necessary for the full optical realization of neural networks. An expanding multiplier scheme is proposed, which, together with common compressing multipliers, is employed to ...
Adrian Stern
doaj   +1 more source

The Effects of Optical Thresholding in Backpropagation Neural Networks

open access: yes
Sigmoid-like activation functions implemented in analog hardware differ in various ways from the standard sigmoidal function as they are asymmetric, truncated, and have a non-standard gain.
Moerland, Perry   +2 more
core  

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