Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)The 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 paper, we study channels and metrics for which those two criteria do and do not coincide for general codes.6211501156Sao Paulo Research Foundation [2013/25977-7]National Science Foundation [DMS-0903517]Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP
In this article we focus on the channel decoding problem in presence of a-priori information. In par...
In this article we focus on the channel decoding problem in presence of a-priori information. In par...
In this paper we describe novel non-statistical Euclidean distance soft-input, soft-output (SISO) de...
FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThe most common decision criteria for d...
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 ...
The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor ...
We present an algorithm that, given a channel, determines if there is a distance for it such that th...
Two channels are equivalent if their maximum likelihood (ML) decoders coincide for every code. We sh...
Abstract—We study the optimal maximum likelihood (ML) block decoding of general binary codes sent ov...
Gaussian inputs and nearest neighbor decoder are optimal choices for the transceiver when perfect ch...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOWe consider two metrics decoding equiva...
This paper studies likelihood decoding for channel coding over discrete memoryless channels. It is s...
In this article we focus on the channel decoding problem in presence of a-priori information. In par...
In this article we focus on the channel decoding problem in presence of a-priori information. In par...
In this paper we describe novel non-statistical Euclidean distance soft-input, soft-output (SISO) de...
FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOThe most common decision criteria for d...
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 ...
The most common decision criteria for decoding are maximum likelihood decoding and nearest neighbor ...
We present an algorithm that, given a channel, determines if there is a distance for it such that th...
Two channels are equivalent if their maximum likelihood (ML) decoders coincide for every code. We sh...
Abstract—We study the optimal maximum likelihood (ML) block decoding of general binary codes sent ov...
Gaussian inputs and nearest neighbor decoder are optimal choices for the transceiver when perfect ch...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
The aim of this paper is to extend some basic concepts related to the Maximum Likelihood decoding of...
FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOWe consider two metrics decoding equiva...
This paper studies likelihood decoding for channel coding over discrete memoryless channels. It is s...
In this article we focus on the channel decoding problem in presence of a-priori information. In par...
In this article we focus on the channel decoding problem in presence of a-priori information. In par...
In this paper we describe novel non-statistical Euclidean distance soft-input, soft-output (SISO) de...