In this paper upper and lower bounds on the probability of decoding failure under maximum likelihood are derived for different (nonbinary) Raptor code constructions. particular four constructions considered; (i) standard construction, (ii) a multi-edge type (iii) construction where is nonbinary but generator matrix LT has only binary entries, (iv) combination (iii). The latter resembles one emp...

In this correspondence we present a new method to convert the maximum-likelihood soft-decision decoding problem for linear block codes into a graph search problem where generalized Dijkstra’s algorithm can still be applied to the decoding procedure. The cost assigned to every branch in the graph is based on a generalization of Wagner rule which is an equivalent form of the maximum-likelihood de...

This correspondence represents two new soft decision decoding algorithms that promise to reduce complexity and at the same time achieve the maximum likelihood decoding (MLD) performance. The first method is an Adaptive Two-Stage Maximum Likelihood Decoder [1] that first estimates a minimum sufficient set and performs decoding within the smaller set to reduce complexity and at the same time achi...

This study investigates a population decoding paradigm in which the maximum likelihood inference is based on an unfaithful decoding model (UMLI). This is usually the case for neural population decoding because the encoding process of the brain is not exactly known or because a simplified decoding model is preferred for saving computational cost. We consider an unfaithful decoding model that neg...

AbstructGeneral symmetric channels are introduced, and near-maximum-likelihood decoding in these channels is studied. First, we define a class of suboptimal decoding algorithms .based on an incomplete search through the code trellis. It is proved that the decoding error probability of suboptimal decoding is bounded above for any q-ary code of length TL and code rate T by twice the error probabi...

The use of digital wireless communication systems has become more and more common during recent years. A multiple-input-multiple-output (MIMO) system using Space-Time Coding techniques can be implemented to enhance the capacity of a wireless link. The optimal decoder is based on the maximum likelihood principle. But as the number of the antennas in the system and the data rates increase, the ma...

We study a population decoding paradigm in which the maximum likelihood inference is based on an unfaithful decoding model (UMLI). This is usually the case for neural population decoding because the encoding process of the brain is not exactly known, or because a simplified decoding model is preferred for saving computational cost. We calculate the decoding error of UMLI and show an example of ...

The use of digital wireless communication systems has become more and more common during recent years. A multiple-input-multiple-output (MIMO) system using Space-Time Coding techniques can be implemented to enhance the capacity of a wireless link. The optimal decoder is based on the maximum likelihood principle. But as the number of the antennas in the system and the data rates increase, the ma...

We propose a new conndence score for decoding and veriication. Since the traditional log likelihood ratio (LLR) is borrowed from speaker veriication technique, it may not be apropriate for decoding because we do not have a good modelling and deenition of LLR for decoding/utterance veriication. We have proposed a new formulation of LLR that can be used for decoding and veriication task. Experime...