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Relevant bibliographies by topics / Adaptive-quantum calculations of arithmetic operations

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Academic literature on the topic 'Adaptive-quantum calculations of arithmetic operations'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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Journal articles on the topic "Adaptive-quantum calculations of arithmetic operations"

1

Filippenko, Igor. "NON-TRADITIONAL CALCULATIONS OF ELEMENTARY MATHEMATICAL OPERATIONS: PART 1. MULTIPLICATION AND DIVISION." EUREKA: Physics and Engineering 4 (July 31, 2018): 49–58. http://dx.doi.org/10.21303/2461-4262.2018.00686.

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Different computational systems are a set of functional units and processors that can work together and exchange data with each other if required. In most cases, data transmission is organized in such a way that enables for the possibility of connecting each node of the system to the other node of the system. Thus, a computer system consists of components for performing arithmetic operations, and an integrated data communication system, which allows for information interaction between the nodes, and combines them into a single unit. When designing a given type of computer systems, problems mig

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2

Igor, Filippenko. "NON-TRADITIONAL CALCULATIONS OF ELEMENTARY MATHEMATICAL OPERATIONS: Part 1. MULTIPLICATION AND DIVISION." EUREKA: Physics and Engineering, no. 4 (July 31, 2018): 49–58. https://doi.org/10.21303/2461-4262.2018.00686.

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Different computational systems are a set of functional units and processors that can work together and exchange data with each other if required. In most cases, data transmission is organized in such a way that enables for the possibility of connecting each node of the system to the other node of the system. Thus, a computer system consists of components for performing arithmetic operations, and an integrated data communication system, which allows for information interaction between the nodes, and combines them into a single unit. When designing a given type of computer systems, problems mig

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3

Zadiraka, Valeriy, Andrii Tereshchenko, and Inna Shvidchenko. "S-Word Arithmetic and High Precision Calculations." Mathematical and computer modelling. Series: Physical and mathematical sciences 25 (September 30, 2024): 70–82. http://dx.doi.org/10.32626/2308-5878.2024-25.70-82.

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The intricacies of using S-word arithmetic, the influence of the value of the parameter S on the estimation of the rounding error are analyzed; what are high-precision calculations and where they are used. The problems of two-key cryptography, computer steganography and the problem of transcomputational complexity are considered as areas of application of S-word arithmetic. For the development of S-word arithmetic algorithms, sequential, parallel, quantum computing models are used, and systems of residual classes are used. The architectural features of the computer system for the implementatio

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4

Han, Xiaojing, Liang Liu, Zhe Zhang, Yufeng Sun, Jiahui Zhou, and Hao Cai. "Design of a High Performance Vector Processor Based on RISIC-V Architecture." Journal of Physics: Conference Series 2560, no. 1 (2023): 012027. http://dx.doi.org/10.1088/1742-6596/2560/1/012027.

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Abstract This paper proposes a high performance Vector processor based on the high performance Embedded Core which is named TS800. The TS800 is a 4-core processor based on RISC-V architecture, implements IMAFDV instruction set, supports L2 Cache, branch prediction, sequential pipeline, and dual-issue structure. The traditional CPU mainly supports Scalar calculations, or only supports Vector calculations. For applications such as image and signal processing, there are a large number of data parallel computing operations. To solve the problem of low performance of parallel data calculations in i

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5

БАРАН, РОМАН. "СИНТЕЗ АДАПТИВНИХ ЧИСЛО-ІМПУЛЬСНИХ ФУНКЦІОНАЛЬНИХ ПЕРЕТВОРЮВАЧІВ ІЗ ЗМІННОЮ РОЗРЯДНІСТЮ". Herald of Khmelnytskyi National University. Technical sciences 349, № 2 (2025): 505–10. https://doi.org/10.31891/2307-5732-2025-349-74.

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The article presents and investigates, for the first time, a method for the structural synthesis of adaptive numerical-impulse functional converters with variable bit width operating in binary code. A new algorithm for their functioning is proposed, utilizing specialized parallel structures that enable efficient parallel computation at the digit and functional block levels. This significantly enhances processing speed compared to known analogs. The developed structural synthesis method is examined using the example of a control system for autonomous vehicles. The proposed methods and tools for

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6

Lin, Yu Pei, and Yong Wang. "Quantum Genetic Optimization of Spindle Speed Ratio in Numerical Control Lathe with Automatic Transmission." Applied Mechanics and Materials 271-272 (December 2012): 1077–81. http://dx.doi.org/10.4028/www.scientific.net/amm.271-272.1077.

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Determination of spindle rotate speed of lathe is an important issue when machine tools with changeable spindle gear ratio cutting metal parts, especially in heavy load cutting. Genetic optimization is used to automate design in engineering application for minimizing volume or weight. A quantum genetic optimization method was applied to calculate rotate speed and ratio of spindle transmission for gain maximum motor efficiency in numerical control lathe. Quantum bit code way was applied to simplify calculation and improve compatibility. Rotate angle strategy gate were introduced to Quantum gate

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7

Najafi, Ali, Behrouz Farhang-Boroujeny, and Ganesh S. Samudra. "A VLSI Design for Implementation of Transform Domain Adaptive Filters." VLSI Design 9, no. 2 (1999): 119–33. http://dx.doi.org/10.1155/1999/87231.

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A VLSI implementation of a dedicated digital signal processor is presented. The processor is tailored for efficient implementation of transform domain adaptive filters. It incorporates a butterfly processor which performs butterfly operation to implement the required transformation. It is also able to perform complex addition, subtraction and multiplication. The butterfly processor makes use of a redundant binary tree multiplier with a recently proposed coding of signed-digit numbers which reduces the number of levels in the tree by one. An on-chip read only memory holds the transformation coe

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8

Chen, Cong Cong, Qing Liu, Lin Bo Tang, Bao Jun Zhao, and Dong Shun Cui. "Implementation of Mean Shift Based on SOPC." Advanced Materials Research 971-973 (June 2014): 534–39. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.534.

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Mean Shift algorithm basedon floating point arithmetic calculation is very difficult to be implemented onreal-time systems. Another problem is that the tracking window of Mean Shift isnot adaptive. In order to solve the problems above, an improved Mean Shiftwhich can be implemented on FPGA is presented. Firstly, Hardware/softwarepartitioning based on the complexity of the algorithm is determined theimplementation of SOPC. Secondly, A pipeline structure is employed for MeanShift algorithm to calculate and accumulate kernel function, shift vector andtarget area in a single clock cycle, and accur

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9

Luo, Qing-bin, Guo-wu Yang, Xiao-yu Li, and Qiang Li. "Quantum reversible circuits for $\mathrm{GF}(2^{8})$ multiplicative inverse." EPJ Quantum Technology 9, no. 1 (2022). http://dx.doi.org/10.1140/epjqt/s40507-022-00144-z.

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AbstractThe synthesis of quantum circuits for multiplicative inverse over $\operatorname{GF}(2^{8})$ GF ( 2 8 ) are discussed in this paper. We first convert the multiplicative inverse operation in $\operatorname{GF}(2^{8})$ GF ( 2 8 ) to arithmetic operations in the composite field $\operatorname{GF}((2^{4})^{2})$ GF ( ( 2 4 ) 2 ) , and then discuss the expressions of the square calculation, the inversion calculation and the multiplication calculation separately in the finite field $\operatorname{GF}(2^{4})$ GF ( 2 4 ) , where the expressions of multiplication calculation in $\operatorname{GF

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10

Nagata, Koji, and Tadao Nakamura. "Mathematical digital quantum computation by means of much more logical skills." Quantum Studies: Mathematics and Foundations, March 11, 2024. http://dx.doi.org/10.1007/s40509-024-00326-7.

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AbstractWe expand Deutsch’s algorithm for determining the mappings of a logical function using four orthogonal states. Using this, we propose a parallel computation for all of the combinations of values in variables of a logical function using sixteen orthogonal states. As an application of our algorithm, we demonstrate two typical arithmetic calculations in the binary system. We study an efficiency for operating a full adder/half adder by quantum-gated computing. The two typical arithmetic calculations are $$(1+1)$$ ( 1 + 1 ) and $$(2+3)$$ ( 2 + 3 ) . The typical arithmetic calculation $$(2+3

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