17718612. WEIGHT CONFIRMATION METHOD FOR AN ANALOG SYNAPTIC DEVICE OF AN ARTIFICIAL NEURAL NETWORK simplified abstract (HYUNDAI MOTOR COMPANY)
WEIGHT CONFIRMATION METHOD FOR AN ANALOG SYNAPTIC DEVICE OF AN ARTIFICIAL NEURAL NETWORK
Organization Name
Inventor(s)
Joon-Hyun Kwon of Hwaseong-si (KR)
Woo-Seok Choi of Hanam-si (KR)
WEIGHT CONFIRMATION METHOD FOR AN ANALOG SYNAPTIC DEVICE OF AN ARTIFICIAL NEURAL NETWORK - A simplified explanation of the abstract
This abstract first appeared for US patent application 17718612 titled 'WEIGHT CONFIRMATION METHOD FOR AN ANALOG SYNAPTIC DEVICE OF AN ARTIFICIAL NEURAL NETWORK
Simplified Explanation
The abstract describes a weight confirmation method for analog synaptic devices in an artificial neural network. The method involves learning the artificial neural network hardware using an artificial neural network learning algorithm and then reading the total weight of a pair of synaptic devices. The total weight is compared with 0, and weights are applied to the positive and negative synaptic devices of the pair. The total weight of the pair is confirmed based on the weights of the positive and negative synaptic devices. This method helps overcome the retention problem of analog synaptic devices, ensuring stable operation of the artificial neural network.
- Learning artificial neural network hardware using analog memory devices and a learning algorithm
- Reading the total weight of a pair of synaptic devices
- Comparing the total weight with 0
- Applying weights to the positive and negative synaptic devices of the pair
- Confirming the total weight based on the weights of the positive and negative synaptic devices
Potential Applications
- Artificial intelligence systems
- Machine learning algorithms
- Neural network hardware
Problems Solved
- Overcoming the retention problem of analog synaptic devices
- Ensuring stable operation of artificial neural networks
Benefits
- Improved stability of artificial neural networks
- Enhanced performance of machine learning algorithms
- Efficient utilization of analog memory devices
Original Abstract Submitted
A weight confirmation method for analog synaptic devices of an artificial neural network includes: learning artificial neural network hardware based on artificial analog memory devices using an artificial neural network learning algorithm; after the learning of the artificial neural network hardware, reading a total weight of a pair of synaptic devices; comparing the total weight of the pair of synaptic devices with 0; applying weights to a positive synaptic device and a negative synaptic device of the pair of synaptic devices, respectively; and confirming the total weight of the pair of synaptic devices in accordance with the weight of the positive synaptic device and the weight of the negative synaptic device. A retention problem of analog synaptic devices is overcome and thus the artificial neural network may stably operate.
