Analog Current-Mode Computational Circuits for Artificial Neural Networks
This book discusses in detail low-voltage low-power designs for minimizing the hardware resources required by neural network implementations. The novel method presented in this book for an accurate realization of activation functions for artificial neural networks (ANNs), is based on specific superi...
-д хадгалсан:
| Үндсэн зохиолч: | |
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| Байгууллагын зохиогч: | |
| Формат: | Цахим Цахим ном |
| Хэл сонгох: | англи |
| Хэвлэсэн: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2025.
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| Хэвлэл: | 1st ed. 2025. |
| Цуврал: | Analog Circuits and Signal Processing,
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| Нөхцлүүд: | |
| Онлайн хандалт: | https://doi.org/10.1007/978-3-032-03989-7 |
| Шошгууд: |
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Агуулга:
- Introduction
- Superior-order approximation functions for generating sigmoidal activation functions
- Superior-order approximation functions for generating radial basis activation functions
- Superior-order approximation functions for artificial neural networks applications
- Analysis and design of analog function synthesizers for implmenting sigmoidal activation functions
- Analysis and design of analog function synthesizers for generating radial basis activation functions
- Analysis and design of analog function synthesizers for artificial neural networks applications
- Low-voltage low-power current-mode CMOS computational circuits for implementing activation functions
- Conclusions.