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关键词： 离散数学   数字电子   离散性   数据结构   二进制  

摘要： 事实上离散数学大致可以被认为是抽象化了的计算机问题,数据结构与算法设计中都能够体现出离散性。计算机里能够表现离散性的问题有很多,因此计算机科学在研究离散数学时有多种选择,这些表现大致都能够被认为是计算机中的二进制。该文主要从离散数学与数字电子、计算机中的离散型问题以及实验仿真三个方面出发,对离散数学和数据结构离散进行了一定的研究和分析[1]。希望可以对有关方面的改善和促进起到一定的借鉴作用和指导意义。

关键词： Java   混合数据结构   教学演示   系统优化  

摘要： Java是一种可以进行跨平台应用程序撰写的面向对象程序设计语言,Java语言的出现给软件系统设计产业带来了深远影响,因此基于Java对混合数据结构教学演示系统进行优化设计。首先要对混合数据结构教学演示系统的框架进行优化设计,然后对教学演示数据库进行优化设计,也就是对数据库表进行优化设计,将本系统与传统教学演示系统进行实验对比,可以发现本系统性能更加卓越。

关键词： Algorithms   Shortest path   Longest common subsequence   Semi-local string comparison  

摘要： For any rectangular grid graph with grid units each potentially having a diagonal edge, we propose a data structure that is constructible in time linear in the number of grid units in the graph and supports linear-time queries of a shortest path between any pair of vertices in the graph. Setting the position of grid units having a diagonal edge appropriately, we can use this data structure to solve a local variant of the longest common subsequence problem or certain related problems in linear time. (C) 2018 Elsevier B.V. All rights reserved.

关键词： 数据结构   信息化教学   目标分级   教学改革  

摘要： 针对信息与计算科学专业的教学实际,分析本专业学生的特点和数据结构课程教学面临的问题,提出将学习目标和实践环节分级,依托"微助教"平台进行信息化教学,通过线上导学、测评、实践指导等环节,优化教学过程,实施对应的分级目标。

关键词： 计算机算法   设计   离散性   数据结构  

摘要： 随着社会发展,信息技术越来越好,计算机算法越来越受到人们的关注。计算机在进行工作的时候,算法是其工作基础,所以计算机算法设计决定了计算机工作的好坏。所谓计算机算法,就是使用数学方法,将信息转换为计算机可以读懂的编码形式,使其功能更容易得到实现。计算机技术在发展的过程中,一些基础知识的支持极其重要,只有把计算机算法与实际操作相结合,计算机才能发展地更好。本文深入分析了计算机算法及数据结构的离散型,以期对计算机方面的研究者有所帮助。

关键词： 算法分析   数据结构  

ISBN: (纸本)9787121350719

摘要： 本书主要介绍各种常用的经典数据结构(如线性表、栈、队列、串、数组、树、图、集合等)和算法，并在时间复杂度和空间复杂度之间进行平衡与取舍。

关键词： Deep learning   Data-structure driven deep neural network (D-SDNN)   Happiness   Happiness-Degree Predictor (H-DP)  

摘要： Background and Objective: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventional methodologies are based on linear relationships, such as the commonly used Multivariate Linear Regression (MLR), which may suffer from the lack of representative capacity to the varied psychological features. Using Deep Neural Networks (DNN), we define a Happiness Degree Predictor (H-DP) based on the answers to five psychometric standardized questionnaires. Methods: A Data-Structure driven architecture for DNNs (D-SDNN) is proposed for defining a HDP in which the network architecture enables the conceptual interpretation of psychological factors associated to happiness. Four different neural network configurations have been tested, varying the number of neurons and the presence or absence of bias in the hidden layers. Two metrics for evaluating the influence of conceptual dimensions have been defined and computed: one quantifies the influence weight of the conceptual dimension in absolute terms and the other one pinpoints the direction (positive or negative) of the influence. Materials: A cross-sectional survey targeting non-institutionalized adult population residing in Spain was completed by 823 cases. The total of 111 elements of the survey are grouped by socio-demographic data and by five psychometric scales (Brief COPE Inventory, EPQR-A, GHQ-28, MOS-SSS and SDHS) measuring several psychological factors acting one as the outcome (SDHS) and the four others as predictors. Results: Our D-SDNN approach provided a better outcome (MSE: 1.46 . 10(-2)) than MLR (MSE: 2.30 . 10(-2)), hence improving by 37% the predictive accuracy, and allowing to simulate the conceptual structure. Conclusions: We observe a better performance of Deep Neural Networks (DNN) with respect to traditional methodologies. This demonstrates its cap

关键词： 数据结构  

ISBN: (纸本)9787563555451

摘要： 本书把数据结构的原理、算法分析和实现有机地结合在一起，系统地介绍各种数据结构及相关算法和应用。全书使用标准C语言作为算法描述语言，通过C语言实现了各种经典算法，能更好地让学生理解各种数据结构算法的原理和应用；分别从逻辑结构、物理结构和算法描述与实现等多个角度系统地介绍了线性表，堆栈与队列，字符串，数组、矩阵和广义表等线性结构，以及二叉树和图等各种非线性结构；从算法应用的角度讨论了各种经典的查找和排序算法；全书共分三部分：第1部分(第1章)为基本概念介绍部分，介绍数据结构、抽象数据类型以及算法的基本概念与知识；第2部分(第2-7章)为基本数据结构部分，重点介绍线性表、堆栈、队列、串、数组与广义表、树与二叉树以及图等各种基本数据结构及其相关算法，并且附有各种算法具体的实现代码；第3部分(第8章和第9章)为算法应用部分，第八章主要介绍各种查找的算法，包括静态查找和动态查找；第九章主要介绍了各种排序算法的原理与应用。全书提供了大量应用实例，并配有大量的插图便于读者理解抽象的算法，另外每章后均附有一定数量编程习题。

关键词： data structures   graph theory   logic circuits   Boolean functions   logic design   quantum computing   logic gates   reversible circuit design   reversible circuit synthesis   AIG-based graph data structure   MIG-based graph data structure   reversible logic synthesis   Boolean function synthesis   quantum technologies   intermediate representations   functional abstraction   truth table   circuit abstraction   binary decision diagram   and-inverter graph   majority inverter graph   cost parameters   graph-based IR  

摘要： Reversible logic synthesis is one of the best suited ways which act as the intermediate step for synthesising Boolean functions on quantum technologies. For a given Boolean function, there are multiple possible intermediate representations (IRs), based on functional abstraction, e.g. truth table, decision diagrams or circuit abstraction, e.g. binary decision diagram (BDD), and-inverter graph (AIG) and majority inverter graph (MIG). These IRs play an important role in building circuits as the choice of an IR directly impacts on cost parameters of the design. In the authors' work, they are analysing the effects of different graph-based IRs (BDD, AIG and MIG) and their usability in making efficient circuit realisations. Although applications of BDDs as an IR to represent large functions has already been studied, here they are demonstrating a synthesis scheme by taking AIG and MIG as IRs and making a comprehensive comparative analysis over all these three graph-based IRs. In experimental evaluation, it is being observed that for small functions BDD gives more compact circuits than the other two IRs but when the input size increases, then MIG as IR makes substantial improvements in cost parameters as compared with BDD by reducing quantum cost by 39% on an average. Along with the experimental results, a detailed analysis over the different IRs is also included to find their easiness in designing circuits.

关键词： C语言   程序设计   数据结构  

ISBN: (纸本)9787563557974

摘要： 本书从抽象数据类型的观点出发，系统全面地介绍了数据结构课程中的基本理论、方法及技巧。全书共分绪论、顺序表、链表、数组和广义表、串、树、图、查找表、内排序、附录1(上机实验)和附录2(数据结构手机学习助手软件使用说明)。书中详细介绍了各种数据结构的定义和性质，详细分析和讨论了这些结构的逻辑特点、存储表示以及在这些结构上定义的一些运算的实现方法及其复杂性分析。在每章的末尾配备了足够的习题，附录对实验内容和自主开发的手机学习助手软件的使用方法作了较详细的介绍。