String (computer science)

About: String (computer science) is a research topic. Over the lifetime, 19430 publications have been published within this topic receiving 333247 citations. The topic is also known as: str & s.

An Efficient Probabilistic Context-Free Parsing Algorithm that Computes Prefix Probabilities

Abstract: We describe an extension of Earley's parser for stochastic context-free grammars that computes the following quantities given a stochastic context-free grammar and an input string: a) probabilities of successive prefixes being generated by the grammar; b) probabilities of substrings being generated by the nonterminals, including the entire string being generated by the grammar; c) most likely (Viterbi) parse of the string; d) posterior expected number of applications of each grammar production, as required for reestimating rule probabilities. (a) and (b) are computed incrementally in a single left-to-right pass over the input. Our algorithm compares favorably to standard bottom-up parsing methods for SCFGs in that it works efficiently on sparse grammars by making use of Earley's top-down control structure. It can process any context-free rule format without conversion to some normal form, and combines computations for (a) through (d) in a single algorithm. Finally, the algorithm has simple extensions for processing partially bracketed inputs, and for finding partial parses and their likelihoods on ungrammatical inputs.

Three-dimensional semiconductor memory device

Abstract: A semiconductor memory device is provided including first and second cell strings formed on a substrate, the first and second cell strings jointly connected to a bit line, wherein each of the first and second cell strings includes a ground selection unit, a memory cell, and first and second string selection units sequentially formed on the substrate to be connected to each other, wherein the ground selection unit is connected to a ground selection line, the memory cell is connected to a word line, the first string selection unit is connected to a first string selection line, and the second string selection unit is connected to a second string selection line, and wherein the second string selection unit of the first cell string has a channel dopant region.

Design of a linguistic statistical decoder for the recognition of continuous speech

Abstract: Most current attempts at automatic speech recognition are formulated in an artificial intelligence framework. In this paper we approach the problem from an information-theoretic point of view. We describe the overall structure of a linguistic statistical decoder (LSD) for the recognition of continuous speech. The input to the decoder is a string of phonetic symbols estimated by an acoustic processor (AP). For each phonetic string, the decoder finds the most likely input sentence. The decoder consists of four major subparts: 1) a statistical model of the language being recognized; 2) a phonemic dictionary and statistical phonological rules characterizing the speaker; 3) a phonetic matching algorithm that computes the similarity between phonetic strings, using the performance characteristics of the AP; 4) a word level search control. The details of each of the subparts and their interaction during the decoding process are discussed.

An efficient probabilistic context-free parsing algorithm that computes prefix probabilities

Abstract: We describe an extension of Earley's parser for stochastic context-free grammars that computes the following quantities given a stochastic context-free grammar and an input string: a) probabilities of successive prefixes being generated by the grammar; b) probabilities of substrings being generated by the nonterminals, including the entire string being generated by the grammar; c) most likely (Viterbi) parse of the string; d) posterior expected number of applications of each grammar production, as required for reestimating rule probabilities. Probabilities (a) and (b) are computed incrementally in a single left-to-right pass over the input. Our algorithm compares favorably to standard bottom-up parsing methods for SCFGs in that it works efficiently on sparse grammars by making use of Earley's top-down control structure. It can process any context-free rule format without conversion to some normal form, and combines computations for (a) through (d) in a single algorithm. Finally, the algorithm has simple extensions for processing partially bracketed inputs, and for finding partial parses and their likelihoods on ungrammatical inputs.

Cooperative adaptive cruise control: Network-aware analysis of string stability

Abstract: In this paper, we consider a Cooperative Adaptive Cruise Control (CACC) system, which regulates intervehicle distances in a vehicle string, for achieving improved traffic flow stability and throughput. Improved performance can be achieved by utilizing information exchange between vehicles through wireless communication in addition to local sensor measurements. However, wireless communication introduces network-induced imperfections, such as transmission delays, due to the limited bandwidth of the network and the fact that multiple nodes are sharing the same medium. Therefore, we approach the design of a CACC system from a Networked Control System (NCS) perspective and present an NCS modeling framework that incorporates the effect of sampling, hold, and network delays that occur due to wireless communication and sampled-data implementation of the CACC controller over this wireless link. Based on this network-aware modeling approach, we develop a technique to study the so-called string stability property of the string, in which vehicles are interconnected by a vehicle following control law and a constant time headway spacing policy. This analysis technique can be used to investigate tradeoffs between CACC performance (string stability) and network specifications (such as delays), which are essential in the multidisciplinary design of CACC controllers. Finally, we demonstrate the validity of the presented framework in practice by experiments performed with CACC-equipped prototype vehicles. cop. 2014 IEEE.