Distributed source coding (DSC) is a new coding paradigm based on two Information Theory results: Slepian-Wolf and Wyner-Ziv theorems. DSC theory relies on the coding of two or more dependent random sequences in an independent way, i.e. associating an independent encoder to each sequence. A single decoder is used to perform joint decoding of all encoded sequences exploiting the statistical depe...

The role of face typicality in face recognition is well established, but it is unclear whether face typicality is important for face evaluation. Prior studies have focused mainly on typicality's influence on attractiveness, although recent studies have cast doubt on its importance for attractiveness judgments. Here, we argue that face typicality is an important factor for social perception beca...

Abstract This paper deals with an important task in legal text processing, namely reference and relation extraction from documents, which includes two subtasks: 1) extraction; 2) determination. Motivated by the fact that subtasks are related share common information, we propose a joint learning model solves simultaneously both subtasks. Our employs Transformer-based encoder-decoder architecture...

This article presents a method to jointly estimate phase and data from a convolutionally coded binary phase-shift keying (BPSK) signal with random phase noise and additive white Gaussian noise (AWGN). The joint receiver–decoder successfully decodes fully suppressed carrier signals in harsh phase-noise environments. A complete description is given of the software implementation, including the ge...

We consider the problem of distributed joint source-channel coding of correlated Gaussian sources over a Gaussian Multiple Access Channel (MAC). There may be side information at the encoders and/or at the decoder. First we specialize a general result in [16] to obtain sufficient conditions for reliable transmission over a Gaussian MAC. This system does not satisfy the source channel separation....

In recent years large scientific interest has been devoted to joint data decoding and parameter estimation techniques. In this paper, iterative turbo decoding joint to channel frequency and phase estimation is proposed. The phase and frequency estimator is embedded into the structure of the turbo decoder itself, keeping into consideration both turbo interleaving and puncturing. Results show tha...

Disorganized speech, or thought disorder, in schizophrenia may reflect abnormal processing of meaningful concepts. To examine whether schizophrenia involves abnormalities in how a meaningful context influences processing of concepts strongly, weakly, or not related to it, we used the N400, an event-related brain potential (ERP) index of semantic relatedness. ERPs were recorded from schizophreni...

Extracting predictions from cosmological theories that describe a multiverse, for what we are likely to observe in our domain, is crucial to establishing the validity of these theories. One way to extract such predictions is from theorygenerated probability distributions that allow for selection effects—generally expressed in terms of assumptions about anthropic conditionalization and how typic...

We propose a method for estimating the musical “typicality” of a song from an information theoretic perspective. While musical similarity compares just two songs, musical typicality quantifies how many of the songs in a set are similar. It can be used not only to express the uniqueness of a song but also to recommend one that is representative of a set. Building on the type theory in informatio...

The closed-loop operation of brain-machine interfaces (BMI) provides a context to discover foundational principles behind human-computer interaction, with emerging clinical applications to stroke, neuromuscular diseases, and trauma. In the canonical BMI, a user controls a prosthetic limb through neural signals that are recorded by electrodes and processed by a decoder into limb movements. In la...