Hardware Implementation of PCM-Based Neurons with Self-Regulating Threshold for Homeostatic Scaling in Unsupervised Learning.
I. Muñoz-MartínStefano BianchiS. HashemkhaniGiacomo PedrettiDaniele IelminiPublished in: ISCAS (2020)
Keyphrases
- hardware implementation
- unsupervised learning
- signal processing
- supervised learning
- efficient implementation
- neural network
- software implementation
- semi supervised
- fpga implementation
- stochastic resonance
- dedicated hardware
- processing elements
- hardware architecture
- image processing algorithms
- model selection
- expectation maximization
- hardware design
- deep architectures
- real time
- low cost
- associative memory
- feature selection
- field programmable gate array
- machine learning
- memory management
- parallel processing
- training data
- computer systems
- pairwise
- image binarization