Results 171 to 180 of about 7,083,147 (335)

Complexity-calibrated benchmarks for machine learning reveal when prediction algorithms succeed and mislead

open access: yesScientific Reports
Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network.
Sarah E. Marzen   +2 more
doaj   +1 more source

Intelligent dynamic sliding-mode neural control using recurrent perturbation fuzzy neural networks

open access: yes, 2016
In this paper, a recurrent perturbation fuzzy neural network (RPFNN) is used to online approximate an unknown nonlinear term in the system dynamics.
Hsu, Chun-Fei; Chang, Chun-Wei
core   +1 more source

Monolithic Oxidation Enables Ultrathin Vertically Graded Tantalum Oxide for Low‐Voltage, Low‐Variability Memristive Switching

open access: yesAdvanced Functional Materials, EarlyView.
Monolithic UV‐ozone oxidation of Ta forms an ultrathin Ta2O5/TaOx bilayer enabling resistive switching with a vertical defect gradient. A stoichiometric surface layer over an oxygen‐deficient sublayer promotes localized filament nucleation near the top interface, enabling low‐voltage operation, and reduced cycle‐to‐cycle variability.
Seunghoon Yang   +11 more
wiley   +1 more source

Multimode Oxide‐Based Optoelectronic Memtransistor for In‐Sensor Vision Processing

open access: yesAdvanced Functional Materials, EarlyView.
A multimode optoelectronic memtransistor (OEMT) is demonstrated for vision explainable artificial intelligence (VXAI) hardware. By integrating optical sensing, electrical masking, and non‐volatile memory, the device enables key operations required for generating saliency information.
Min Gu Lee   +10 more
wiley   +1 more source

Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons [PDF]

open access: yes, 2007
Chicca E, Indiveri G, Douglas RJ. Context dependent amplification of both rate and event-correlation in a VLSI network of spiking neurons. Presented at the Advances in Neural Information Processing Systems 19 (NIPS).Cooperative competitive networks are ...
Schölkopf, B.   +5 more
core  

Bio‐Derived Polyelectrolyte Additive–Induced Interfacial Ion‐Diffusion Barriers for Nonvolatile Organic Artificial Synapses

open access: yesAdvanced Functional Materials, EarlyView.
Sodium alginate regulates interfacial ion transport and retention in electrolyte‐gated synaptic transistors. The carboxylate‐rich polymeric network forms a dynamic interfacial ion‐diffusion barrier that facilitates ion injection during programming while suppressing ion back‐diffusion, thereby stabilizing the electrochemically doped channel state.
Chaeyeon Han   +6 more
wiley   +1 more source

Noise‐Limited Bit Precision in Ferroelectric Synaptic Transistors for High‐Resolution Neuromorphic Computing

open access: yesAdvanced Functional Materials, EarlyView.
Low‐frequency noise spectroscopy defines the resolvable conductance states of synaptic FeFETs by coupling read‐current fluctuation with usable dynamic range. The resulting noise‐limited bit precision establishes a universal, device‐agnostic reliability metric beyond the memory window, enabling quantitative benchmarking and rational design of high ...
Jaehong Park   +12 more
wiley   +1 more source

Light‐Induced Field‐Tunneling Synapses in Solution‐Processed Van Der Waals Heterostructures for Scalable, Retina‐Inspired Optical Sensing

open access: yesAdvanced Functional Materials, EarlyView.
A scalable, solution‐processed WSe2/ZrO2‐x van der Waals heterostructure realizes a light‐induced field‐tunneling synapse (LIFTS) that activates exclusively under bright illumination, emulating the photopic adaptation of the human retina at the device level.
Kijeong Nam   +10 more
wiley   +1 more source

Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing

open access: yesAdvanced Functional Materials, EarlyView.
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin   +7 more
wiley   +1 more source

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

open access: yesAdvanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan   +4 more
wiley   +1 more source

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