Studies on programming features and methods of floating gate mosfet as analog memory for synaptic weights in neural networks

1992 ◽  
Vol 9 (4) ◽  
pp. 350-357
Author(s):  
Wang Yang ◽  
Li Zhijian ◽  
Shi Bingxue
Keyword(s):  
Neural Networks ◽  
Floating Gate ◽  
Analog Memory

A floating-gate analog memory device for neural networks

1993 ◽  
Vol 40 (11) ◽  
pp. 2029-2035 ◽  
Author(s):  
O. Fujita ◽  
Y. Amemiya
Keyword(s):  
Neural Networks ◽  
Memory Device ◽  
Floating Gate ◽  
Analog Memory

scholarly journals Single-Poly Floating-Gate Memory Cell Options for Analog Neural Networks

2021 ◽  
pp. 108062
Author(s):  
Maksym Paliy ◽  
Tommaso Rizzo ◽  
Piero Ruiu ◽  
Sebastiano Strangio ◽  
Giuseppe Iannaccone
Keyword(s):  
Neural Networks ◽  
Memory Cell ◽  
Floating Gate ◽  
Floating Gate Memory ◽  
Analog Neural Networks

scholarly journals Using Floating-Gate Memory to Train Ideal Accuracy Neural Networks

2019 ◽  
Vol 5 (1) ◽  
pp. 52-57 ◽  
Author(s):  
Sapan Agarwal ◽  
Diana Garland ◽  
John Niroula ◽  
Robin B. Jacobs-Gedrim ◽  
Alex Hsia ◽  
...  
Keyword(s):  
Neural Networks ◽  
Floating Gate ◽  
Floating Gate Memory

Quasiperiodic-Chaotic Neural Networks and Short-Term Analog Memory

2021 ◽  
Vol 31 (01) ◽  
pp. 2130003
Author(s):  
Natsuhiro Ichinose
Keyword(s):  
Neural Networks ◽  
Visual Memory ◽  
Large Scale ◽  
Quasiperiodic Solution ◽  
Short Term ◽  
Chaotic Neural Networks ◽  
Analog Memory ◽  
Short Term Visual Memory ◽  
Potential Applications ◽  
Chaotic Neuron

A model of quasiperiodic-chaotic neural networks is proposed on the basis of chaotic neural networks. A quasiperiodic-chaotic neuron exhibits quasiperiodic dynamics that an original chaotic neuron does not have. Quasiperiodic and chaotic solutions are exclusively isolated in the parameter space. The chaotic domain can be identified by the presence of a folding structure of an invariant closed curve. Using the property that the influence of perturbation is conserved in the quasiperiodic solution, we demonstrate short-term visual memory in which real numbers are acceptable for representing colors. The quasiperiodic solution is sensitive to dynamical noise when images are restored. However, the quasiperiodic synchronization among neurons can reduce the influence of noise. Short-term analog memory using quasiperiodicity is important in that it can directly store analog quantities. The quasiperiodic-chaotic neural networks are shown to work as large-scale analog storage arrays. This type of analog memory has potential applications to analog computation such as deep learning.

Inference of Deep Neural Networks with Analog Memory Devices

2020 ◽  
Author(s):  
Stefano Ambrogio ◽  
Pritish Narayanan ◽  
Hsinyu Tsai ◽  
Charles Mackin ◽  
Katherine Spoon ◽  
...  
Keyword(s):  
Neural Networks ◽  
Deep Neural Networks ◽  
Memory Devices ◽  
Analog Memory
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