Add to ORKGThe most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor decoding. It is well-known that maximum likelihood decoding coincides with nearest neighbor decoding with respect to the Hamming metric on the binary symmetric channel. In this work we study channels and metrics for which those two criteria do and do not coincide for general codes
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
Abstract- Bounded distance soft decoders guar-antee correct decoding at least up to half the mini-mu...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor ...
The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor ...
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)The most common decision criteria for d...
FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThe most common decision criteria for d...
We present an algorithm that, given a channel, determines if there is a distance for it such that th...
Almost all nonbinary codes were designed for the Hamming metric. The Lee metric was defined by Lee i...
Two channels are equivalent if their maximum likelihood (ML) decoders coincide for every code. We sh...
It is well known that for Gaussian channels, a nearest neighbor decoding rule, which seeks the minim...
Abstract—”THIS PAPER IS ELIGIBLE FOR THE STU-DENT PAPER AWARD”. Reliable transmission over a discret...
This paper studies likelihood decoding for channel coding over discrete memoryless channels. It is s...
In this paper we consider the additive white Gaussian noise channel with an average input power cons...
Abstract—We study the optimal maximum likelihood (ML) block decoding of general binary codes sent ov...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
Abstract- Bounded distance soft decoders guar-antee correct decoding at least up to half the mini-mu...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor ...
The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor ...
Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)The most common decision criteria for d...
FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThe most common decision criteria for d...
We present an algorithm that, given a channel, determines if there is a distance for it such that th...
Almost all nonbinary codes were designed for the Hamming metric. The Lee metric was defined by Lee i...
Two channels are equivalent if their maximum likelihood (ML) decoders coincide for every code. We sh...
It is well known that for Gaussian channels, a nearest neighbor decoding rule, which seeks the minim...
Abstract—”THIS PAPER IS ELIGIBLE FOR THE STU-DENT PAPER AWARD”. Reliable transmission over a discret...
This paper studies likelihood decoding for channel coding over discrete memoryless channels. It is s...
In this paper we consider the additive white Gaussian noise channel with an average input power cons...
Abstract—We study the optimal maximum likelihood (ML) block decoding of general binary codes sent ov...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
Abstract- Bounded distance soft decoders guar-antee correct decoding at least up to half the mini-mu...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...