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A New Scheme to Construct Orthogonal Channel Matrix for MIMO STBC by Givens Rotation
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作者 Huanming Zhang Kaiyi Xian +1 位作者 Lijun Feng Chaokang Hu 《Journal of Signal and Information Processing》 2016年第1期34-38,共5页
This paper proposes a scheme to construct orthogonal channel matrix for full rate quasiorthogonal STBC based on givens rotation with lower bit error rate. The transmission diversity method rotates every single informa... This paper proposes a scheme to construct orthogonal channel matrix for full rate quasiorthogonal STBC based on givens rotation with lower bit error rate. The transmission diversity method rotates every single information symbol. The scheme can suppress channel noise and eliminate the interference term well. Simulation results show that the method can improve performance better than conventional algorithm without increasing decoding complexity. 展开更多
关键词 QO-STBC MIMO givens rotation
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基于改进QR算法的矩阵分解器设计 被引量:1
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作者 陈文杰 宋宇鲲 张多利 《电子科技》 2022年第11期21-28,共8页
矩阵分解是矩阵求逆中重要的运算之一,被广泛运用在神经网络、数字信号处理、无线通信技术等领域中。针对传统的分解算法运算不利于硬件实现的缺陷,文中在一种列向量优化QR分解算法的基础上,提出了一种一维线性矩阵分解结构,并完成了其A... 矩阵分解是矩阵求逆中重要的运算之一,被广泛运用在神经网络、数字信号处理、无线通信技术等领域中。针对传统的分解算法运算不利于硬件实现的缺陷,文中在一种列向量优化QR分解算法的基础上,提出了一种一维线性矩阵分解结构,并完成了其ASIC设计。该分解器支持2~32阶矩阵分解运算,在TSMC 28 nm工艺下工作主频为700 MHz。仿真和FPGA测试结果表明,该分解器与MATLAB运算结果的相对误差小于10^(-12)。在执行12阶级以上规模矩阵分解时,该分解器的运算周期相比传统一维线性结构具有2.3倍的加速比。在执行32阶矩阵分解时,该分解器的运算周期相比于NIVIDA RTX2070具有22.8倍的加速比。 展开更多
关键词 矩阵分解 QR分解 givens旋转 Column-wise givens rotation FPGA实现 硬件加速 一维线性结构 ASIC实现
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Prediction of Time Series Empowered with a Novel SREKRLS Algorithm 被引量:3
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作者 Bilal Shoaib Yasir Javed +6 位作者 Muhammad Adnan Khan Fahad Ahmad Rizwan Majeed Muhammad Saqib Nawaz Muhammad Adeel Ashraf Abid Iqbal Muhammad Idrees 《Computers, Materials & Continua》 SCIE EI 2021年第5期1413-1427,共15页
For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article.The proposed algorithm lends itself ... For the unforced dynamical non-linear state–space model,a new Q1 and efficient square root extended kernel recursive least square estimation algorithm is developed in this article.The proposed algorithm lends itself towards the parallel implementation as in the FPGA systems.With the help of an ortho-normal triangularization method,which relies on numerically stable givens rotation,matrix inversion causes a computational burden,is reduced.Matrix computation possesses many excellent numerical properties such as singularity,symmetry,skew symmetry,and triangularity is achieved by using this algorithm.The proposed method is validated for the prediction of stationary and non-stationary Mackey–Glass Time Series,along with that a component in the x-direction of the Lorenz Times Series is also predicted to illustrate its usefulness.By the learning curves regarding mean square error(MSE)are witnessed for demonstration with prediction performance of the proposed algorithm from where it’s concluded that the proposed algorithm performs better than EKRLS.This new SREKRLS based design positively offers an innovative era towards non-linear systolic arrays,which is efficient in developing very-large-scale integration(VLSI)applications with non-linear input data.Multiple experiments are carried out to validate the reliability,effectiveness,and applicability of the proposed algorithm and with different noise levels compared to the Extended kernel recursive least-squares(EKRLS)algorithm. 展开更多
关键词 Kernel methods square root adaptive filtering givens rotation mackey glass time series prediction recursive least squares kernel recursive least squares extended kernel recursive least squares square root extended kernel recursive least squares algorithm
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Effective Methods of QR-Decompositions of Square Complex Matrices by Fast Discrete Signal-Induced Heap Transforms
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作者 Artyom M. Grigoryan 《Advances in Linear Algebra & Matrix Theory》 2022年第4期87-110,共24页
The purpose of this work is to present an effective tool for computing different QR-decompositions of a complex nonsingular square matrix. The concept of the discrete signal-induced heap transform (DsiHT, Grigoryan 20... The purpose of this work is to present an effective tool for computing different QR-decompositions of a complex nonsingular square matrix. The concept of the discrete signal-induced heap transform (DsiHT, Grigoryan 2006) is used. This transform is fast, has a unique algorithm for any length of the input vector/signal and can be used with different complex basic 2 × 2 transforms. The DsiHT is zeroing all components of the input signal while moving or heaping the energy of the signal to one component, for instance the first one. We describe three different types of QR-decompositions that use the basic transforms with the T, G, and M-type complex matrices we introduce, as well as without matrices but using analytical formulas. We also present the mixed QR-decomposition, when different type DsiHTs are used in different stages of the algorithm. The number of such decompositions is greater than 3<sup>(N-1)</sup>, for an N × N complex matrix. Examples of the QR-decomposition are described in detail for the 4 × 4 and 6 × 6 complex matrices and compared with the known method of Householder transforms. The precision of the QR-decompositions of N × N matrices, when N are 6, 13, 17, 19, 21, 40, 64, 100, 128, 201, 256, and 400 is also compared. The MATLAB-based scripts of the codes for QR-decompositions by the described DsiHTs are given. 展开更多
关键词 QR Decomposition Signal-Induced Heap Transform Householder Transform givens rotations
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