This article studies the joint roles of similarity and frequency in determining graded category structure. Perceptual classification learning experiments were conducted in which presentation frequencies of individual exemplars were manipulated. The exemplars had varying degrees of similarity to members of the target and contrast categories. Classification accuracy and typicality ratings increas...

We discuss Boltzmann’s probabilistic explanation of the second law of thermodynamics, providing a comprehensive presentation of what is called today the typicality account. Countering its misconception as an alternative explanation, we examine the relation between Boltzmann’s H-theorem and the general typicality argument, demonstrating the conceptual continuity between the two. We then discuss ...

We examine the influence of contrast categories on the internal graded membership structure of natural language categories. To this end we contrast two exemplar models in their account of typicality: According to the GCM, typicality is the summed similarity towards all category members. According to the SDGCM, typicality is determined by both the summed similarity towards all category members a...

Two experiments were directed at distinguishing associative and similarity-based accounts of systematic differences in categorization time for different items in natural categories. Experiment 1 investigated the correlation of categorization time with three measures of instance centrality in a category. Production frequency (PF), rated typicality, and familiarity from category norms for British...

In the absence of a fundamental theory that precisely predicts values for observable parameters, anthropic reasoning attempts to constrain probability distributions over those parameters in order to facilitate the extraction of testable predictions. The utility of this approach has been vigorously debated of late, particularly in light of theories that claim we live in a multiverse, where param...

Semi-definite relaxation (SDR) has been shown to have the capability of approaching maximum-likelihood (ML) performance. In this work, we first develop a new SDR-based detector that jointly uses forward error correction (FEC) code information in the detection stage. The joint SDR detector substantially improves overall receiver performance by generating highly reliable information to downstream...

We consider the problem of distributed joint source-channel coding of correlated Gaussian sources over a Gaussian Multiple Access Channel (GMAC). There may be side information at the decoder and/or at the encoders. First we specialize a general result in [20] to obtain sufficient conditions for reliable transmission over a Gaussian MAC. This system does not satisfy the source-channel separation...

Tree-based translation models, which exploit the linguistic syntax of source language, usually separate decoding into two steps: parsing and translation. Although this separation makes tree-based decoding simple and efficient, its translation performance is usually limited by the number of parse trees offered by parser. Alternatively, we propose to parse and translate jointly by casting tree-ba...

This thesis is devoted to several efficient VLSI architecture design issues in errorcorrecting coding, including finite field arithmetic, (Generalized) Low-Density ParityCheck (LDPC) codes, and Reed-Solomon codes. A systematic low-complexity bit-parallel finite field multiplier design approach is proposed. This design approach is applicable to GF (2m) constructed by arbitrary irreducible polyno...

‘Don Quixote’ is a new accusation process for Tardos traitor tracing codes which is, as far as we know, the first practical implementation of joint decoding. The first key idea is to iteratively prune the list of potential colluders to keep the computational effort tractable while going from single, to pair,. . . to t-subset joint decoding. At the same time, we include users accused in previous...