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EDA Challenges for Memristor-Crossbar based Neuromorphic Computing
2015
Proceedings of the 25th edition on Great Lakes Symposium on VLSI - GLSVLSI '15
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In this paper, we summarize some of our recent published works about enhancing the design robustness and efficiency of memristor crossbar based NCS. ...
Discovery of memristor further accelerates engineering realization of NCS by leveraging the similarity between synaptic connections in neural networks and programming weight of the memristor. ...
In OLD training, amplitudes and durations of the programming signals are first computed based on different algorithms and applications. Then the memristors in the crossbar are programmed accordingly. ...
doi:10.1145/2742060.2743754
dblp:conf/glvlsi/LiuWCLWH15
fatcat:adxca5gmdvflfmasygaglwvrem
RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonics
[article]
2022
arXiv
pre-print
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As many of these applications are employed in real-time scenarios, accelerating RNN/LSTM/GRU inference is crucial. ...
In recent years, newer RNN variants, such as GRUs and LSTMs, have been used for implementing these applications. ...
ACKNOWLEDGMENT This work was supported by National Science Foundation (NSF), through grants CCF-1813370 and CCF-2006788. ...
arXiv:2209.00084v1
fatcat:y7o5yp2fqfeizd7vmd5lg47u5a
A Novel Fractional-Order Memristive Chaotic Circuit with Coexisting Double-Layout Four-Scroll Attractors and Its Application in Visually Meaningful Image Encryption
2023
Symmetry
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The characteristics of the memristor, dynamic mechanism of oscillation, and behaviors of the proposed system were analyzed, and then a visually meaningful image encryption scheme was designed based on ...
Finally, a visually meaningful image encryption scheme based on the proposed system was designed, and its security was assessed by statistical analysis and different attacks. ...
The chaos diagrams of the system (8) based on the C0 algorithm and the spectral entropy algorithm are shown in Figure 22 . ...
doi:10.3390/sym15071398
fatcat:wppsckt6v5bntevioigw7auari
2020 Index IEEE Transactions on Cybernetics Vol. 50
2020
IEEE Transactions on Cybernetics
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., and Gao, H., Reference Trajectory Reshaping Optimi-zation and Control of Robotic Exoskeletons for Human-Robot Co-Manipulation; TCYB Aug. 2020 3740-3751 Wu, X., Jiang, B., Yu, K., Miao, c., and Chen, ...
., +, TCYB July 2020 2971-2981 Adaptive Synchronization of Reaction-Diffusion Neural Networks and Its Application to Secure Communication. ...
Barrier Lyapunov Function-Based Adaptive Fuzzy FTC for Switched Systems and Its Applications to Resistance-Inductance-Capacitance Circuit System. ...
doi:10.1109/tcyb.2020.3047216
fatcat:5giw32c2u5h23fu4drupnh644a
2021 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 32
2021
IEEE Transactions on Neural Networks and Learning Systems
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The primary entry includes the coauthors' names, the title of the paper or other item, and its location, specified by the publication abbreviation, year, month, and inclusive pagination. ...
The Subject Index contains entries describing the item under all appropriate subject headings, plus the first author's name, the publication abbreviation, month, and year, and inclusive pages. ...
Cumulative Permuted Fractional Entropy and its Applications. ...
doi:10.1109/tnnls.2021.3134132
fatcat:2e7comcq2fhrziselptjubwjme
Parameter Estimation and Classification via Supervised Learning in the Wireless Physical Layer: A Survey and Tutorial
2021
IEEE Access
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In our review of state-of-the-art works, we found significant use of SL algorithms in the following PHY layer applications: Dynamic Spectrum Access (DSA), channel corrections, Automatic Gain Control (AGC ...
achieve low costs via inexpensive forward-pass computations, attain flexible operations due to trainable parameters, and yield accurate results based on the universal approximator attribute. ...
TABLE 12 : 12 A summary of SL-based PHY-layer applications and associated open challenges. ...
doi:10.1109/access.2021.3128813
fatcat:kj6xxdefzbbttanqdlwgq7ekqq
Recent Advances in Convolutional Neural Network Acceleration
[article]
2018
arXiv
pre-print
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Therefore, it is necessary and urgent to implement CNN in a faster way. ...
We also analyze the acceleration methods in terms of CNN architecture compression, algorithm optimization, and hardware-based improvement. ...
W can be replaced by the product of two full rank matrices U · V with size m × r and r × n respectively. ...
arXiv:1807.08596v1
fatcat:jx66ekaofjhqzdbaueal476bvi
Mathematical Operations and Equation Solving with Reconfigurable Metadevices
[article]
2022
arXiv
pre-print
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Their equation-solving capabilities are applied only to matrices with special spectral (eigenvalue) distribution. ...
Here we report the theory and design of wave-based metastructures using tunable elements capable of solving integral/differential equations in a fully-reconfigurable fashion. ...
Acknowledgements This work was supported in part by the US Air Force Office of Scientific Research (AFOSR) Multidisciplinary University Research Initiative (MURI) grant number FA9550-17-1-0002. ...
arXiv:2206.02549v1
fatcat:jcvqcuaz2jbvdkmbs6wmmqdlvu
Dual-edged sword of ion migration in perovskite materials for simultaneous energy harvesting and storage application
2023
iScience
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Portable electronic devices and Internet of Things (IoT) require an uninterrupted power supply for their optimum performance and are key ingredients of the futuristic smart buildings - cities. ...
Toward this narrative, in this viewpoint, we shed light on application of disruptive organic-inorganic hybrid halide perovskite bifunctional materials employed as smart photo-rechargeable energy devices ...
However, if
ll OPEN ACCESS employed in charge storage application, the same ion migration characteristics of HHPs pave a way for manufacturing advanced bifunctional devices, memristors, transistors and ...
doi:10.1016/j.isci.2023.108172
pmid:37927552
pmcid:PMC10622710
fatcat:ewmsp5oznndjhnpdmia6zcty4a
The Goldilocks Principle of Learning Unitaries by Interlacing Fixed Operators with Programmable Phase Shifters on a Photonic Chip
[article]
2024
arXiv
pre-print
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Programmable photonic integrated circuits represent an emerging technology that amalgamates photonics and electronics, paving the way for light-based information processing at high speeds and low power ...
We explore this criterion for different photonic components, including photonic waveguide lattices and meshes of directional couplers, which allows the identification of several families of photonic components ...
Indeed, random matrix theory establishes robust criteria for studying random complex-valued matrices at the limit of large dimensions based on the singular value decomposition (SVD) of the same 53 . ...
arXiv:2403.10469v1
fatcat:h3xwr67qrvhm5phfpvx6yf3fty
2014 Index IEEE Transactions on Neural Networks and Learning Systems Vol. 25
2014
IEEE Transactions on Neural Networks and Learning Systems
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., +, TNNLS Dec. 2014 2288-2294
Matrix decomposition
A Fast Algorithm for Nonnegative Matrix Factorization and Its Conver-
gence. ...
., +, TNNLS Dec. 2014 2202-2211
Multiwavelet Packet Entropy and its Application in Transmission Line Fault
Recognition and Classification. ...
The Field of Values of a Matrix and Neural Networks. Georgiou, G.M., TNNLS Sep. 2014 ...
doi:10.1109/tnnls.2015.2396731
fatcat:ztnfcozrejhhfdwg7t2f5xlype
Binarization Methods for Motor-Imagery Brain-Computer Interface Classification
[article]
2020
arXiv
pre-print
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Successful motor-imagery brain-computer interface (MI-BCI) algorithms either extract a large number of handcrafted features and train a classifier, or combine feature extraction and classification within ...
Our first method, based on sparse bipolar random projection, projects a large number of real-valued Riemannian covariance features to a binary space, where a linear SVM classifier can be learned with binary ...
We estimate the number of MACs of a matrix logarithm based on the complexity of an optimized Householder transformation (O(8n 3 c /3)) [38] and the iterative QR decomposition using implicit Wilkinson ...
arXiv:2010.07004v1
fatcat:yt3jnaftyzdq7k3ogxnt4vazwy
Photonic kernel machine learning for ultrafast spectral analysis
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2110.15241v1 fatcat:7ct4qy3jsvdnbjyxfuxq4lmtgm
We theoretically describe some of the key underlying principles, and then numerically illustrate the reached performances on a photonic lattice-based implementation. ...
The approach combines the versatility of machine learning and the speed of photonic hardware to reach unprecedented throughput rates. ...
ACKNOWLEDGMENTS This work was supported by the ERC Consolidator grant NOMLI No. 770933, by ANR via the project UNIQ, and the FET flagship project PhoQuS (grant agreement ID No. 820392). ...
arXiv:2110.15241v2
fatcat:6zvz3eyoejafzngd4zspaigsya
2019 Index IEEE Transactions on Circuits and Systems I: Regular Papers Vol. 66
2019
IEEE Transactions on Circuits and Systems Part 1: Regular Papers
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Kenarangi, F., +, TCSI Nov. 2019 4356-4367 On Learning With Nonlinear Memristor-Based Neural Network and its Replication. ...
Asynchronous Finite-Time Filtering of Networked Switched Systems and its Application: an Event-Driven Method. ...
Analysis of SRAM Enhancements Through Sense Amplifier ...
doi:10.1109/tcsi.2020.2966967
fatcat:f663jj5g45e3peggn3gwn5jys4
TraNNsformer: Neural network transformation for memristive crossbar based neuromorphic system design
2017
2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)
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2017 pre-print arXiv:1708.07949v1 fatcat:nuws22v5dbbizeyehl4ah6gnfiOther Versions
Subsequently, it retrains the network to fine tune the connections and reinforce the clusters. ...
Eventually they produce DNNs with highly inefficient hardware realizations (in terms of area and energy). ...
Memristors are programmable resistors and can encode the synaptic weights of the DNN. ...
doi:10.1109/iccad.2017.8203823
dblp:conf/iccad/AnkitS017
fatcat:gd4i2wzberb5bgbbv4czuvdv24
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