• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.657-667
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• 2019

This paper studies synthetic aperture radar (SAR) imaging problem which the scatterers are often distributed in block sparse pattern. To exploiting the sparse geometrical feature, a Kronecker constrained SAR imaging algorithm is proposed by combining the block sparse characteristics with the multiway sparse reconstruction framework with Tucker modeling. We validate the proposed algorithm via real data and it shows that the our algorithm can achieve better accuracy and convergence than the reference methods even in the demanding environment. Meanwhile, the complexity is smaller than that of the existing methods. The simulation experiments confirmed the effectiveness of the algorithm as well.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.289-297
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• 1994

A block design will be said to have Property C if the concordance matrix can be expressed as a linear combination of Kronecker product of permutation matrices. No matrix inversions are necessary for the intrablock analysis of the block designs which possesses the Property C(Paik, 1985). In this paper, in order to show the Li type PBIB designs possesses the Property C, we suggest the structure of the concordance matrices of Li type PBIB designs are multi-nested block circulant pattern.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1223-1228
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• 2006

This paper presents an experimental investigation of a recently developed Kronecker Product (KP) method to determine the type, location, and intensity of structural damage from an identified state-space model of the system. Although this inverse problem appears to be highly nonlinear, the system mass, stiffness, and damping matrices are identified through a series of transformations, and with the aid of the Kronecker product, only linear operations are involved in the process. Since a state-space model can be identified directly from input-output data, an initial finite element model and/or model updating are not required. The test structure is a two-degree-of-freedom torsional system in which mass and stiffness are arbitrarily adjustable to simulate various conditions of structural damage. This simple apparatus demonstrates the capability of the damage detection method by not only identifying the location and the extent of the damage, but also differentiating the nature of the damage. The potential applicability of the KP method for structural damage identification is confirmed by laboratory test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1618-1637
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• 2018

By means of compressive sensing (CS) technique, this paper considers the collection of sensor data with spatiotemporal correlations in wireless sensor networks (WSNs). In energy-constrained WSNs, one-dimensional CS methods need a lot of data transmissions since they are less applicable in fully exploiting the spatiotemporal correlations, while the Kronecker CS (KCS) methods suffer performance degradations when the signal dimension increases. In this paper, an appropriate sensing matrix as well as an efficient sensing method is proposed to further reduce the data transmissions without the loss of the recovery performance. Different matrices for the temporal signal of each sensor node are separately designed. The corresponding energy-efficient data gathering method is presented, which only transmitting a subset of sensor readings to recover data of the entire WSN. Theoretical analysis indicates that the sensing structure could have the relatively small mutual coherence according to the selection of matrix. Compared with the existing spatiotemporal CS (CS-ST) method, the simulation results show that the proposed efficient measurement method could reduce data transmissions by about 25% with the similar recovery performance. In addition, compared with the conventional KCS method, for 95% successful recovery, the proposed sensing structure could improve the recovery performance by about 20%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.788-794
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• 2005

In this paper, we focus on the potential of dual polarized antennas in mobile system. thus, this paper designs exact dual polarized channel with Spatial Channel Model (SCM) and investigates the performance for certain environment. Using proposed the channel model; we know estimates of the channel capacity as a function of cross polarization discrimination (XPD) and spatial fading correlation. It is important that the MIMO channel matrix consists of Kronecker product dividable spatial and polarized channel. Through the channel characteristics, we propose an algorithm for the adaptation of transmit antenna configuration to time varying propagation environments. The optimal active transmit antenna subset is determined with equal power allocated to the active transmit antennas, assuming no feedback information on types of the selected antennas. We first consider a heuristic decision strategy in which the optimal active transmit antenna subset and its system capacity are determined such that the transmission data rate is maximized among all possible types. This paper then proposes singular values decision procedure consisting of Kronecker product with spatial and polarize channel. This method of singular value decision, which the first channel environments is determined using singular values of spatial channel part which is made of environment parameters and distance between antennas. level of correlation. Then we will select antenna which have various polarization type. After spatial channel structure is decided, we contact polarization types which have considerable cases It is note that the proposed algorithms and analysis of dual polarized channel using SCM (Spatial Channel Model) optimize channel capacity and reduce the number of transmit antenna selection compare to heuristic method which has considerable 100 cases.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.12
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• pp.1878-1888
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• 1990

In this paper, the input-output interconnection method of the multi-valued signal processing circuit using perfect Shuffle technique and Kronecker product is discussed. Using this method, the design method of circuit of the multi-valued Reed-Muller expansions(MRME) to be used the multi-valued signal processing on finite field GF(p**m) is presented. The proposed input-output interconnection method is shown that the matrix transform is efficient and that the module structure is easy. The circuit design of MRME on FG(p**m) is realized following as` 1) contructing the baisc gates on GF(3) by CMOS T gate, 2) designing the basic cells to be implemented the transform and inverse transform matrix of MRME using these basic gates, 3) interconnecting these cells by the input-output interconnecting method of the multivalued signal processing circuits. Also, the circuit design of the multi-valued signal processing function on GF(3\ulcorner similar to Winograd algorithm of 3x3 array of DFT (discrete fourier transform) is realized by interconnection of Perfect Shuffle technique and Kronecker product. The presented multi-valued signal processing circuits that are simple and regular for wire routing and posses the properties of concurrency and modularity are suitable for VLSI.

• The Transactions of the Korea Information Processing Society
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• v.6 no.3
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• pp.781-791
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• 1999

DD(Decision Diagrams) is an efficient operational data structure for an optimal expression of boolean functions. In a graph-based synthesis using DD, the goal of optimization decreases representation space for boolean functions. This paper represents boolean functions using OPKFDD(Ordered Pseudo-Kronecker Functional Decision Diagrams) for a graph-based synthesis and is based on the number of nodes as the criterion of DD size. For a property of OPKFDD that is able to select one of different decomposition types for each node, OPKFDD is variable in its size by the decomposition types selection of each node and input variable order. This paper proposes a method for generating OPKFDD efficiently from the current BDD(Binary Decision Diagram) Data structure and an algorithm for minimizing one. In the multiple output functions, the relations of each function affect the number of nodes of OPKFDD. Therefore this paper proposes a method to decide the input variable order considering the above cases. Experimental results of comparing with the current representation methods and the reordering methods for deciding input variable order are shown.

• Journal of applied mathematics & informatics
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• v.32 no.3_4
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• pp.529-537
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• 2014

The paper introduces a new product of polynomials defined over a field. It is a generalization of the ordinary product with inner polynomial getting non-overlapping segments obtained by multiplying with coefficients and variable with expanding powers. It has been called 'Ordered Power Product' (OPP). Considering two rings of polynomials $R_m[x]=F[x]modulox^m-1$ and $R_n[x]=F[x]modulox^n-1$, over a field F, the paper then considers the newly introduced product of the two polynomial rings. Properties and algebraic structure of the product of two rings of polynomials are studied and it is shown to be a ring. Using the new type of product of polynomials, we define a new product of two cyclic codes and devise a method of getting a cyclic code from the 'ordered power product' of two cyclic codes. Conditions for the OPP of the generators polynomials of component codes, giving a cyclic code are examined. It is shown that OPP cyclic code so obtained is more efficient than the one that can be obtained by Kronecker type of product of the same component codes.

• Advances in nano research
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• v.16 no.3
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• pp.231-249
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• 2024

When the amplitude of the vibrations is equivalent to that clearance, the vibrations for small amplitudes will really be significantly nonlinear. Nonlinearities will not be significant for amplitudes that are rather modest. Finally, nonlinearities will become crucial once again for big amplitudes. Therefore, the concrete panel system may experience a big amplitude in this work as a result of the high temperature. Based on the 3D modeling of the shell theory, the current work shows the influences of the von Kármán strain-displacement kinematic nonlinearity on the constitutive laws of the structure. The system's governing Equations in the nonlinear form are solved using Kronecker and Hadamard products, the discretization of Equations on the space domain, and Duffing-type Equations. Thermo-elasticity Equations. are used to represent the system's temperature. The harmonic solution technique for the displacement domain and the multiple-scale approach for the time domain are both covered in the section on solution procedures for solving nonlinear Equations. An effective data-driven solution is often utilized to predict how different systems would behave. The number of hidden layers and the learning rate are two hyperparameters for the network that are often chosen manually when required. Additionally, the data-driven method is offered for addressing the nonlinear vibration issue in order to reduce the computing cost of the current study. The conclusions of the present study may be validated by contrasting them with those of data-driven solutions and other published articles. The findings show that certain physical and geometrical characteristics have a significant effect on the existing concrete panel structure's susceptibility to temperature change and GPL weight fraction. For building construction industries, several useful recommendations for improving the thermo-mechanics' behavior of structural concrete panels are presented.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.203-211
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• 2016

The genetic code is a key to bio-informatics and to a science of biological self-organizing on the whole. Modern science faces the necessity of understanding and systematically explaining mysterious features of ensembles of molecular structures of the genetic code. This paper is devoted to symmetrical analysis for genetic systems. Mathematical theories of noise-immunity coding and discrete signal processing are based on Jacket matrix methods of representation and analysis of information. Both of the RNA and Jacket Matrix property also have the Element(Block) - wise Inverse Matrices. These matrix methods, which are connected closely with relations of symmetry, are borrowed for a matrix analysis of ensembles of molecular elements of the genetic code. This method is presented for its simplicity and the clarity with which it decomposes a Jacket Matrix in terms of the genetic RNA Codon.