We have developed a complementary pair of pFET and nFET floating-gate silicon MOS transistors for analog learning applications. The memory storage is nonvolatile; hot-electron injection and electron tunneling permit bidirectional memory updates. Because these updates depend on both the stored memory value and the transistor terminal voltages, the synapses can implement a learning function. We have derived a memory-update rule for both devices, and have shown that the synapse learning follows a simple power law. Unlike conventional EEPROMs, the synapses allow simultaneous memory reading and writing. Synapse transistor arrays can therefore compute both the array output, and local memory updates, in parallel. We have fabricated prototype ...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor trans...
Synapses plays an important role of learning in a neural network; the learning rules which modify th...
We have developed a complementary pair of pFET and nFET floating-gate silicon MOS transistors for an...
We have developed a new floating-gate silicon MOS transistor for analog learning applications. The m...
Our goal is to develop silicon learning systems. One impediment to achieving this goal has been the ...
We describe single-transistor silicon synapses that compute, learn, and provide non-volatile memory ...
We describe single-transistor silicon synapses that compute, learn, and provide non-volatile memory ...
A computation is an operation that can be performed by a physical machine. We are familiar with digi...
We have demonstrated on-chip learning in an array of floating-gate MOS synapse transistors. The arra...
Compared to modern supercomputers, which consume roughly 10^6 W of power, the human brain requires o...
A 3-transistor non-volatile analog storage cell with 14 bits effective resolution and rail-to-rail b...
We propose a CMOS architecture for spiking neural networks with permanent memory and online learning...
In this work, a study on a semi-floating-gate synaptic transistor (SFGST) is performed to verify its...
The explosive growth of data and information has motivated technological developments in computing s...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor trans...
Synapses plays an important role of learning in a neural network; the learning rules which modify th...
We have developed a complementary pair of pFET and nFET floating-gate silicon MOS transistors for an...
We have developed a new floating-gate silicon MOS transistor for analog learning applications. The m...
Our goal is to develop silicon learning systems. One impediment to achieving this goal has been the ...
We describe single-transistor silicon synapses that compute, learn, and provide non-volatile memory ...
We describe single-transistor silicon synapses that compute, learn, and provide non-volatile memory ...
A computation is an operation that can be performed by a physical machine. We are familiar with digi...
We have demonstrated on-chip learning in an array of floating-gate MOS synapse transistors. The arra...
Compared to modern supercomputers, which consume roughly 10^6 W of power, the human brain requires o...
A 3-transistor non-volatile analog storage cell with 14 bits effective resolution and rail-to-rail b...
We propose a CMOS architecture for spiking neural networks with permanent memory and online learning...
In this work, a study on a semi-floating-gate synaptic transistor (SFGST) is performed to verify its...
The explosive growth of data and information has motivated technological developments in computing s...
NOTE: Text or symbols not renderable in plain ASCII are indicated by [...]. Abstract is included in ...
This work presents an analog neuromorphic synapse device consisting of two oxide semiconductor trans...
Synapses plays an important role of learning in a neural network; the learning rules which modify th...