L'informatica neuromorfa è un campo interdisciplinare che progetta sistemi hardware e software ispirati alla struttura e al funzionamento delle reti neurali biologiche, in particolare del cervello umano. Utilizza architetture non-von Neumann, in cui processori e memoria sono strettamente integrati, consentendo una computazione massicciamente parallela, un'elaborazione delle informazioni guidata dagli eventi e un funzionamento a basso consumo. Utilizzando elementi come neuroni spike e sinapsi artificiali, i sistemi neuromorfi imitano i meccanismi cerebrali di apprendimento, adattamento ed elaborazione sensoriale.
Questa è la nostra ultima selezione di prodotti in tutto il mondo pubblicazioni and patents in english on Neuromorphic Computing, between many scientific online journals, classified and focused on neuromorphic computing, spiking rete neuraleNeurone leaky integrate-and-fire, memristor, neuromorfo, plasticità sinaptica, ritardo assonale, neurone al silicio, VLSI analogico, apprendimento hebbiano e spiking neurale.
Compact Nonvolatile Reconfigurable Mode Converter by Sb2S3 Embedded in 4H-Silicon-Carbide-on-Insulator Platform
Published on 2025-05-01 by Danfeng Zhu, Junbo Chen, Shaobin Qiu, Dingnan Deng, Jinming Luo @MDPI
Abstract: Nonvolatile switching is emerging and shows potential in integrated optics. A compact nonvolatile reconfigurable mode converter implemented on a 4H-silicon-carbide-on-insulator (4H-SiCOI) platform with a footprint of 0.5 × 1 × 1.8 μm3 is proposed in this study. The functional region features an Sb2S3 film embedded in a 4H-SiC strip waveguide. The functionality is achieved through manipulating the phase state of the Sb2S3. The high refractive index contrast [...]
Our summary: Compact nonvolatile reconfigurable mode converter implemented on a 4H-SiCOI platform with high efficiency mode conversion. Functional region features Sb2S3 film embedded in 4H-SiC strip waveguide, achieving high transmittance and mode purity. Device exhibits robustness and potential for large communication capacity in neuromorphic optical computing.
Nonvolatile, Reconfigurable, Mode Converter, 4H-Silicon-Carbide-on-Insulator
Publication
Ternary Heterojunction Synaptic Transistors Based on Perovskite Quantum Dots
Published on 2025-05-01 by Shuqiong Lan, Jinkui Si, Wangying Xu, Lan Yang, Jierui Lin, Chen Wu @MDPI
Abstract: The traditional von Neumann architecture encounters significant limitations in computational efficiency and energy consumption, driving the development of neuromorphic devices. The optoelectronic synaptic device serves as a fundamental hardware foundation for the realization of neuromorphic computing and plays a pivotal role in the development of neuromorphic chips. This study develops a ternary heterojunction synaptic transistor based on perovskite quantum dots to tackle the critical challenge [...]
Our summary: Development of ternary heterojunction synaptic transistor based on perovskite quantum dots for synaptic weight modulation. Enhanced hysteresis window and effective carrier trapping modulation. Emulation of photonic synaptic behaviors for high-performance optoelectronic synaptic transistors.
Perovskite Quantum Dots, Ternary Heterojunction, Synaptic Transistors, Neuromorphic Computing
Publication
An Evolutionary Dendritic Neuron Model
Published on 2025-04-29 by Chongyuan Wang, Huiyi Liu @MDPI
Abstract: Conventional deep learning models rely heavily on the McCulloch–Pitts (MCP) neuron, limiting their interpretability and biological plausibility. The Dendritic Neuron Model (DNM) offers a more realistic alternative by simulating nonlinear and compartmentalized processing within dendritic branches, enabling efficient and transparent learning. While DNMs have shown strong performance in various tasks, their learning capacity at the single-neuron level remains underexplored. This paper[...]
Our summary: Evolutionary Dendritic Neuron Model proposing RDE algorithm for enhancing synaptic plasticity. Outperforms conventional methods in accuracy, generalization, and convergence. Supports societal applications like medical diagnostics and financial screening.
Dendritic Neuron Model, Reinforced Dynamic-grouping Differential Evolution, synaptic plasticity, evolutionary learning
Publication
Method and apparatus for evaluating neuronal connectivity using a memristor
Patent published on the 2025-04-24 in WO under Ref WO2025085259 by PRESIDENT AND FELLOWS OF HARVARD COLLEGE [US] (Ham Donhee [us], Kim Seokjoo [us], Kim Hanju [us], Wang Jun [us])
Abstract: Methods and apparatuses are provided for evaluating a communication pathway connection. One of the methods includes generating a first voltage trace based on voltage peaks of a first node of a pair of nodes, the first voltage trace comprising a plurality of first voltage bursts over a period of time, the first voltage bursts each comprising a positive component and a negative component; generating a second voltage trace based on voltage peaks of a second node of the pair of nodes, the second vol[...]
Our summary: Evaluation of neuronal connectivity using memristor technology, methods for assessing communication pathway connection, determining strength of communication pathway based on conductance changes.
memristor, neuronal connectivity, conductance, communication pathway
Patent
Temporal kernel device, temporal kernel computing system, and method for operating device and system
Patent published on the 2025-03-06 in WO under Ref WO2025048591 by SEOUL NATIONAL UNIV R&DB FOUNDATION [KR] (Hwang Cheol Seong [kr], Jang Yoon Ho [kr], Shim Sung Keun [kr])
Abstract: Disclosed are a temporal kernel device, a temporal kernel computing system comprising same, and a method for operating the device and system. The disclosed temporal kernel device may comprise one or more temporal kernel cell structures, wherein each of the temporal kernel cell structures may comprise a first nonvolatile memristor, and a second nonvolatile memristor and a capacitor connected in parallel to each other, wherein the second nonvolatile memristor and the capacitor connected in paralle[...]
Our summary: Temporal kernel device with cell structures comprising nonvolatile memristors and capacitors connected in parallel and series.
temporal kernel device, temporal kernel computing system, method, operating device
Patent
Neuron circuit
Patent published on the 2025-02-19 in EP under Ref EP4510043 by GUDE MICHAEL [DE] (Gude Michael [de])
Abstract: Convolutional neural networks (CNN) or spiking neural networks (SNN) are usually applied for implementation. Although CNNs can be realized purely digitally, they require a lot of energy due to the high processing power (MAC structures). SNNs can usually only be implemented with analog components and are therefore difficult to implement in circuits with a technology node below 10 nm.The present disclosure is aimed to realize electronic neurons that process pulse-width modulated signals. These neu[...]
Our summary: Implementation of electronic neurons processing pulse-width modulated signals, Advantages of combining neurons with FPGA, Configuring FPGA for forwarding signals and weight data.
Neuron circuit, Convolutional neural networks, Spiking neural networks, FPGA
Patent
Dynamics Research of the Hopfield Neural Network Based on Hyperbolic Tangent Memristor with Absolute Value
Published on 2025-02-17 by Huiyan Gao, Hongmei Xu @MDPI
Abstract: Neurons in the brain are interconnected through synapses. Local active memristors can both simulate the synaptic behavior of neurons and the action potentials of neurons. Currently, the hyperbolic tangent function-type memristors used for coupling neural networks do not belong to local active memristors. To take advantage of local active memristors and consider the multi-equilibrium point problem, a cosine function is introduced into the state equation, resulting in the design of an absolute val[...]
Our summary: Research explores dynamics of a Hopfield Neural Network using a new type of memristor with absolute value, showing rich dynamical behaviors and hardware feasibility.
Hopfield Neural Network, Hyperbolic Tangent Memristor, Absolute Value, Dynamics
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