A basic operation of pattern recognition is to find the nearest match between an input-data word of W bit length and a number R of reference-data words [1]. For fast and efficient integration of the nearest-match func-tion a fully-parallel associative-memory has been pro-posed recently [2]. In this fully-parallel associative memory, the search time is primarily determined by the performance of a circuit called winner-line-up amplifier (WLA). The prime goal of the WLA circuitry is to amplify the distance between the winner and the near-est-loser sufficiently so that the following win-ner-take-all (WTA) circuit can decide the winner at bi-nary logic level. Because of the internal capacitances and resistances in the MOS transistors, there is a...
Abstract—A minimum distance search engine (MDSE) is presented as a hardware accelerator for various ...
Heittmann A, Rückert U. Mixed Mode VLSI Implementation of a Neural Associative Memory. Analog Integr...
In this paper we present an energy efficient match-line (ML) sensing scheme for high-speed ternary c...
Pattern recognition and learning are basic functions, which are needed to build artificial systems w...
In this paper, we present a new concept and its circuit implemen-tation for high-speed associative m...
[[abstract]]The parallel processing elements (PPE) have been built around an associative memory (AM)...
Nearest neighbor search is a very active field in machine learning. It appears in many application c...
A parallel associative processor is formed from a DRAM circuit whose storage positions are organized...
International audienceAssociative memories aim at matching an input noisy vector with a stored one. ...
We present a new concept and its circuit implementation for a high-speed and low-voltage associative...
The associative memory (AM) chip is ASIC device specifically designed to perform ``pattern matching'...
[[abstract]]This paper presents a novel algorithm for the field programmable gate array (FPGA) reali...
An analog MOS circuit is proposed for implementing a Lotka–Volterra (LV) competitive neural network ...
We propose a new generation of VLSI processor for pattern recognition based on Associative Memory ar...
Pattern matching algorithms, which may be realized via associative memories, require further improve...
Abstract—A minimum distance search engine (MDSE) is presented as a hardware accelerator for various ...
Heittmann A, Rückert U. Mixed Mode VLSI Implementation of a Neural Associative Memory. Analog Integr...
In this paper we present an energy efficient match-line (ML) sensing scheme for high-speed ternary c...
Pattern recognition and learning are basic functions, which are needed to build artificial systems w...
In this paper, we present a new concept and its circuit implemen-tation for high-speed associative m...
[[abstract]]The parallel processing elements (PPE) have been built around an associative memory (AM)...
Nearest neighbor search is a very active field in machine learning. It appears in many application c...
A parallel associative processor is formed from a DRAM circuit whose storage positions are organized...
International audienceAssociative memories aim at matching an input noisy vector with a stored one. ...
We present a new concept and its circuit implementation for a high-speed and low-voltage associative...
The associative memory (AM) chip is ASIC device specifically designed to perform ``pattern matching'...
[[abstract]]This paper presents a novel algorithm for the field programmable gate array (FPGA) reali...
An analog MOS circuit is proposed for implementing a Lotka–Volterra (LV) competitive neural network ...
We propose a new generation of VLSI processor for pattern recognition based on Associative Memory ar...
Pattern matching algorithms, which may be realized via associative memories, require further improve...
Abstract—A minimum distance search engine (MDSE) is presented as a hardware accelerator for various ...
Heittmann A, Rückert U. Mixed Mode VLSI Implementation of a Neural Associative Memory. Analog Integr...
In this paper we present an energy efficient match-line (ML) sensing scheme for high-speed ternary c...