检索结果-内蒙古大学图书馆

Towards new multiwavelets: Associated filters and algorithms. Part I: Theoretical framework and investigation of biomedical signals, ECG and coronavirus cases

学校读者我要写书评

暂无评论

arXiv 2021年

作者： Jallouli, Malika Zemni, Makerem Mabrouk, Anouar Ben Mahjoub, Mohamed Ali Université de Sousse Ecole Nationale d’Ingénieurs de Sousse LATIS Laboratory of Advanced Technology and Intelligent Systems Sousse4023 Tunisia Department of Mathematics Higher Institute of Applied Mathematics and Computer Science Street of Assad Ibn Alfourat Kairouan3100 Tunisia Laboratory of Algebra Number Theory and Nonlinear Analysis LR18ES15 Department of Mathematics Faculty of Sciences Monastir5000 Tunisia Department of Mathematics Faculty of Sciences University of Tabuk Saudi Arabia

Biosignals are nowadays important subjects for scientific researches from both theory and applications especially with the appearance of new pandemics threatening the humanity such as the new Coronavirus. One aim in the present work is to prove that Wavelets may be a successful machinery to understand such phenomena by applying a step forward extension of wavelets to multiwavelets. We proposed in a first step to improve multiwavelet notion by constructing more general families using independent components for multi-scaling and multiwavelet mother functions. A special multiwavelet is then introduced, continuous and discrete multiwavelet transforms are associated, as well as new filters and algorithms of decomposition and reconstruction. The constructed multiwavelet framework is applied for some experimentations showing fast algorithms, ECG signal and a strain of Coronavirus *** Codes 42C40, 65T60, 94A08 © 2021, CC0.

关键词： Coronavirus

Fundamental causal bounds of quantum random access memories

学校读者我要写书评

暂无评论

arXiv 2023年

作者： Wang, Yunfei Alexeev, Yuri Jiang, Liang Chong, Frederic T. Liu, Junyu Martin A. Fisher School of Physics Brandeis University WalthamMA02453 United States Computational Science Division Argonne National Laboratory LemontIL60439 United States Chicago Quantum Exchange ChicagoIL60637 United States Department of Computer Science The University of Chicago ChicagoIL60637 United States Pritzker School of Molecular Engineering The University of Chicago ChicagoIL60637 United States Kadanoff Center for Theoretical Physics The University of Chicago ChicagoIL60637 United States qBraid Co. ChicagoIL60615 United States SeQure ChicagoIL60615 United States

Quantum devices should operate in adherence to quantum physics principles. Quantum random access memory (QRAM), a fundamental component of many essential quantum algorithms for tasks such as linear algebra, data search, and machine learning, is often proposed to offer O(log N) circuit depth for O(N) data size, given N qubits. However, this claim appears to breach the principle of relativity when dealing with a large number of qubits in quantum materials interacting locally. In our study we critically explore the intrinsic bounds of rapid quantum memories based on causality, employing the relativistic quantum field theory and Lieb–Robinson bounds in quantum many-body systems. In this paper, we consider a hardware-efficient QRAM design in hybrid quantum acoustic systems. Assuming clock cycle times of approximately 10−3 seconds and a lattice spacing of about 1 micrometer, we show that QRAM can accommodate up to O(107) logical qubits in 1 dimension, O(1015) to O(1020) in various 2D architectures, and O(1024) in 3 dimensions. We contend that this causality bound broadly applies to other quantum hardware systems. Our findings highlight the impact of fundamental quantum physics constraints on the long-term performance of quantum computing applications in data science and suggest potential quantum memory designs for performance enhancement. Copyright © 2023, The Authors. All rights reserved.

关键词： Linear algebra

Quartic scaling second-order approximate coupled cluster singles and doubles via tensor hypercontraction: THC-CC2

学校读者我要写书评

暂无评论

JOURNAL OF CHEMICAL PHYSICS 2013年第12期138卷 124111-124111页

作者： Hohenstein, Edward G. Kokkila, Sara I. L. Parrish, Robert M. Martinez, Todd J. Stanford Univ Dept Chem Stanford CA 94305 USA Stanford Univ PULSE Inst Stanford CA 94305 USA SLAC Natl Accelerator Lab Menlo Pk CA 94025 USA Georgia Inst Technol Sch Chem & Biochem Ctr Computat Mol Sci & Technol Atlanta GA 30332 USA

The second-order approximate coupled cluster singles and doubles method (CC2) is a valuable tool in electronic structure theory. Although the density fitting approximation has been successful in extending CC2 to larger molecules, it cannot address the steep O(N-5) scaling with the number of basis functions, N. Here, we introduce the tensor hypercontraction (THC) approximation to CC2 (THC-CC2), which reduces the scaling to O(N-4) and the storage requirements to O(N-2). We present an algorithm to efficiently evaluate the THC-CC2 correlation energy and demonstrate its quartic scaling. This implementation of THC-CC2 uses a grid-based least-squares THC (LS-THC) approximation to the density-fitted electron repulsion integrals. The accuracy of the CC2 correlation energy under these approximations is shown to be suitable for most practical applications. (C) 2013 American Institute of Physics. [http://***/10.1063/1.4795514]

关键词： ELECTRONIC structure LEAST squares APPROXIMATION theory TENSOR algebra ALGORITHMS ELECTRONS

Schaum's outline of theory and problems of essential computer mathematics /

学校读者我要写书评

暂无评论

Topological coding and topological matrices toward network overall security

1982年

作者： Lipschutz Seymour.

来源：内蒙古大学图书馆图书评论

学校读者我要写书评

暂无评论

arXiv 2019年

作者： Yao, Bing Zhao, Meimei Zhang, Xiaohui Mu, Yarong Sun, Yirong Zhang, Mingjun Yang, Sihua Ma, Fei Su, Jing Wang, Xiaomin Wang, Hongyu Sun, Hui College of Mathematics and Statistics Northwest Normal University Lanzhou730070 China College of Science Gansu Agricultural University Lanzhou730070 China College of Mathematics and Statistics Jishou University Jishou Hunan416000 China School of Information Engineering Lanzhou University of Finance and Economics Lanzhou730030 China School of Electronics Engineering and Computer Science Peking University Beijing100871 China School of Electronics and Information Engineering Lanzhou Jiaotong University Lanzhou730070 China

A mathematical topology with matrix is a natural representation of a coding relational structure that is found in many fields of the world. Matrices are very important in computation of real applications, s ce matrices are easy saved in computer and run quickly, as well as matrices are convenient to deal with communities of current networks, such as Laplacian matrices, adjacent matrices in graph theory. Motivated from convenient, useful and powerful matrices used in computation and investigation of today’s networks, we have introduced Topcode-matrices, which are matrices of order 3 × q and differ from popular matrices applied in linear algebra and computer science. Topcode-matrices can use numbers, letters, Chinese characters, sets, graphs, algebraic groups etc. as their elements. One important thing is that Topcode-matrices of numbers can derive easily number strings, since number strings are text-based passwords used in information security. Topcode-matrices can be used to describe topological graphic passwords (Topsnut-gpws) used in information security and graph connected properties for solving some problems coming in the investigation of Graph Networks and Graph Neural Networks proposed by GoogleBrain and DeepMind. Our topics, in this article, are: Topsnut-matrices, Topcode-matrices, Hanzi-matrices, adjacency ve-value matrices and pan-Topcode-matrices, and some connections between these Topcode-matrices will be proven. We will discuss algebraic groups obtained from the above matrices, graph groups, graph networking groups and number string groups for encrypting different communities of dynamic networks. The operations and results on our matrices help us to set up our overall security mechanism to protect networks. Copyright © 2019, The Authors. All rights reserved.

关键词： Graph theory

学校读者我要写书评

暂无评论

D-S证据推理的决策问题

计算机工程与应用 2003年第33期39卷 82-84,97页

作者：刁联旺李勇智杨静宇南京理工大学计算机系南京200094 南京林业大学信息学院南京210037

在处理不确定信息的方法中,D-S证据推理性能突出,应用广泛。但也存在决策方面的困难,事实上,有效的决策方法仍是它未解决的问题之一。该文从两方面研究了这一问题。首先根据测度论中代数(域)扩张理论,引入决策命题集的概念,对决策命题... 详细信息

在处理不确定信息的方法中,D-S证据推理性能突出,应用广泛。但也存在决策方面的困难,事实上,有效的决策方法仍是它未解决的问题之一。该文从两方面研究了这一问题。首先根据测度论中代数(域)扩张理论,引入决策命题集的概念,对决策命题加以约束;其次分析了现有的决策方法,对线性加权组合决策方法提出了改进,并结合应用实例给出了详细可行的算法。

关键词： D-S证据理论信任函数似真函数决策

q-means: A quantum algorithm for unsupervised machine learning

学校读者我要写书评

暂无评论

arXiv 2018年

作者： Kerenidis, Iordanis Landman, Jonas Luongo, Alessandro Prakash, Anupam CNRS IRIF Université Paris Diderot Paris France Centre for Quantum Technologies National University of Singapore Singapore Ecole Polytechnique Palaiseau France Atos Bull Les Clayes Sous Bois France

Quantum machine learning is one of the most promising applications of a full-scale quantum computer. Over the past few years, many quantum machine learning algorithms have been proposed that can potentially offer considerable speedups over the corresponding classical algorithms. In this paper, we introduce q-means, a new quantum algorithm for clustering which is a canonical problem in unsupervised machine learning. The q-means algorithm has convergence and precision guarantees similar to k-means, and it outputs with high probability a good approximation of the k cluster centroids like the classical algorithm. Given a dataset of N d-dimensional vectors vi (seen as a matrix V ∈ RN×d) stored in QRAM, the running time of q-means is Oe ( kdδη2 κ(V )(µ(V ) + kηδ) + k2 ηδ125 κ(V )µ(V ) ) per iteration, where κ(V ) is the condition number, µ(V ) is a parameter that appears in quantum linear algebra procedures and η = maxi kvik2. For a natural notion of well-clusterable datasets, the running time becomes Oe ( k2dηδ235 + k2.5 ηδ32 ) per iteration, which is linear in the number of features d, and polynomial in the rank k, the maximum square norm η and the error parameter δ. Both running times are only polylogarithmic in the number of datapoints N. Our algorithm provides substantial savings compared to the classical k-means algorithm that runs in time O(kdN) per iteration, particularly for the case of large datasets. © 2018, CC BY-NC-SA.

关键词： Quantum theory

theory and application of GF(2/sup p/) cellular automata as on-chip test pattern generator

学校读者我要写书评

暂无评论

Theory and application of GF(2/sup p/) cellular automata as ...

International Conference on VLSI Design

作者： B.K. Sikdar K. Paul G.P. Biswas V. Boppana C. Yang S. Mukherjee P.P. Chaudhuri Fujitsu Laboratories of America Inc. Sunnyvale CA USA

This paper sets a new direction for test solution of VLSI circuits. The solution is based on the theory of extension field-that is, extension of finite field commonly referred to as Galois field (GF). The GF(2) with the set {0,1} traditionally employed in the digital domain has been extended in the present work to GF(2/sup p/) with elements from the set {0,1,2,...,2/sup p-1/}. The conventional on-chip LFSR/cellular automata (CA) based test pattern generators built around GF(2) elements have been replaced with the cellular structure of CF(2/sup p/) CA. The inter-cell connections and the value of p of a regular, modular and cascadable structure of GF(2/sup p/) CA can be tuned to maximize the fault coverage in a CUT (circuit under test). Availability of RTL/functional description of the CUT leads to a better tuning. The fault coverage figures obtained with GF(2/sup p/) CA based test pattern generator on the benchmark circuits and a few commercial circuits can be found to be significantly better than the best results reported so far with LFSR, GLFSR or GF(2) CA. The small set of uncovered faults can be handled with the introduction of a limited number of observation and test points. Area overhead for CATPG can be significantly reduced through the scheme of folding introduced in this paper.

关键词： Test pattern generators Built-in self-test Circuit testing Circuit faults Automatic testing Galois fields Benchmark testing algebra polynomials computer science

Review of Recent Systems for Detecting and Diagnosing Pronunciation Errors

学校读者我要写书评

暂无评论

Review of Recent Systems for Detecting and Diagnosing Pronun...

International Conference on Advanced Systems and Electric Technologies (IC_ASET)

作者： Karim Dabbabi Abdelkarim Mars Faculty of Sciences of Tunis Research Unite of Analysis and Processing of Electrical and Energetic Systems Tunis Tunisia Research Laboratory in Algebra Number Theory and Intelligent Systems Faculty of Sciences of Monastir Monastir Tunisia

Nowadays, computer Aided Language Learning (CALL) frameworks have attracted a lot of attention because of their capability, adaptability, and flexibility in improving people's language skills. The field of Mispronunciation Detection and Diagnosis (MDD) is considered one of the applications of these frameworks and has recently benefited from the rapid innovation spawned in deep learning models and different acoustic, phonetic, and linguistic features. The various manner of combinations of different features and deep learning architectures for different MDD systems require huge amount of annotated textual data to be pretrained and hence achieved good performances. However, providing a large amount of annotated textual data for pre-training is a tedious and time-consuming operation. For this, a pre-trained acoustic model from unannotated data can be a good alternative. In this article, we present different MDD systems categorized according to the pre-training mode: pre-trained approaches without annotated text data and pre-trained approaches with annotated text data. Experimental results, advantages, disadvantages and additional improvements for each method explored for each category are presented and discussed.

关键词：