Abstract- Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of applications involving industrial as well as consumer appliances. This is particularly the case when low power consumption, small size and/or very high speed are required. This approach exploits the computational features of Neural Networks, the implementation efficiency of analog VLSI circuits and the adaptation capabilities of the on-chip learning feedback schema. High-speed video cameras are powerful tools for investigating for instance the biomechanics analysis or the movements of mechanical parts in manufacturing processes. In the past years, the use of CMOS sensors instead of CCDs has enabled the development of high-speed video c...
Analog VLSI implementations of artificial neural networks are usually considered efficient for the s...
Biological systems process the analog signals such as image and sound efficiently. To process the in...
This thesis introduces a novel approach to the design of circuits found in a very large scale integr...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
In this paper we present an analog VLSI architecture that implements a neural network for image proc...
We have designed a fully-integrated analog CMOS cognitive image sensor based on a two-layer artifici...
We present the study of an analog hardware accelerator targeting the implementation of on-chip Neura...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
This paper deals with analog VLSI architectures addressed to the implementation of smart adaptive sy...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
In this chapter, we introduce an analog chip hosting a self-learning neural network with local learn...
We present architectures, CMOS circuits and CMOS chips to process image flows at very high speed. Th...
We propose an analog Neural Network ASIC where computations are implemented in 0.35-µm CMOS technolo...
A fully connected artificial neural network (NN) for color identification (with 125 neurons and 11 c...
Analog VLSI implementations of artificial neural networks are usually considered efficient for the s...
Biological systems process the analog signals such as image and sound efficiently. To process the in...
This thesis introduces a novel approach to the design of circuits found in a very large scale integr...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
In this paper we present an analog VLSI architecture that implements a neural network for image proc...
We have designed a fully-integrated analog CMOS cognitive image sensor based on a two-layer artifici...
We present the study of an analog hardware accelerator targeting the implementation of on-chip Neura...
Analog VLSI on-chip learning Neural Networks represent a mature technology for a large number of app...
This paper deals with analog VLSI architectures addressed to the implementation of smart adaptive sy...
Abstract — This paper presents a compact architecture for analog CMOS hardware implementation of vol...
In this chapter, we introduce an analog chip hosting a self-learning neural network with local learn...
We present architectures, CMOS circuits and CMOS chips to process image flows at very high speed. Th...
We propose an analog Neural Network ASIC where computations are implemented in 0.35-µm CMOS technolo...
A fully connected artificial neural network (NN) for color identification (with 125 neurons and 11 c...
Analog VLSI implementations of artificial neural networks are usually considered efficient for the s...
Biological systems process the analog signals such as image and sound efficiently. To process the in...
This thesis introduces a novel approach to the design of circuits found in a very large scale integr...