• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.5C
• /
• pp.521-526
• /
• 2009

In this paper, a complex-valued recursive least squares escalator filter algorithm with reduced computational complexity for complex-valued signal processing applications is presented. The local tap weight of RLS-ESC algorithm is updated by incrementing its old value by an amount equal to the local estimation error times the local gain scalar, and for the gain scalar, the local input autocorrelation is calculated at the previous time. By deriving a new gain scalar that can be calculated by using the current local input autocorrelation, reduced computational complexity is accomplished. Compared with the computational complexity of the complex-valued version of RLS-ESC algorithm, the computational complexity of the proposed method can be reduced by 50% without performance degradation. The reduced computational complexity of the proposed algorithm is even less than that of the LMS-ESC. Simulation results for complex channel equalization in 64QAM modulation schemes demonstrate that the proposed algorithm has superior convergence and constellation performance.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1994.10a
• /
• pp.25-30
• /
• 1994

A vector algorithm for calculating the stiffness matrices of reinforced concrete shell elements is presented. The algorithm is based on establishing vector lengths equal to the number of elements. The computational efficiency of the proposed algorithm is assessed on a Cray Y-MP supercomputer. It is shown that the vector algorithm achieves scalar-to-vector speedup of 1.7 to 7.6 on three inelastic problems.

• The Journal of the Acoustical Society of Korea
• /
• v.19 no.2E
• /
• pp.27-31
• /
• 2000

Evaluating log-likelihood of Gaussian mixture density is major computational burden for the keyword spotting system using continuous HMM. In this paper, we employ the bucket box intersection (BBI) algorithm to reduce the computational complexity of keyword spotting. We make some modification in implementing BBI algorithm in order to increase the discrimination ability among the keyword models. According to our keyword spotting experiments, the modified BBI algorithm reduces 50% of log-likelihood computations without performance degradation, while the original BBI algorithm under the same condition reduces only 30% of log-likelihood computations.

• Journal of applied mathematics & informatics
• /
• v.19 no.1_2
• /
• pp.105-125
• /
• 2005

Motivated by the field experimental designs in agriculture, the theory of block designs has been applied to several areas such as statistics, combinatorics, communication networks, distributed systems, cryptography, etc. An explicit formula and its fast computational algorithm for a class of symmetric balanced incomplete block designs are presented. Based on the formula and the careful investigation of the modulus multiplication table, the algorithm is developed. The computational costs of the algorithm is superior to those of the conventional ones.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 1999.10a
• /
• pp.411-420
• /
• 1999

The computational model and a new eigenvalue solution algorithm for large-scale structures is presented in the form of parallel computation. The computational loads and data storages required during the solution process are drastically reduced by evenly distributing computational loads to each processor. As the parallel computational model, multiple personal computers are connected by 10Mbits per second Ethernet card. In this study substructuring techniques and static condensation method are adopted for modeling a large-scale structure. To reduce the size of an eigenvalue problem the interface degrees of freedom and one lateral degree of freedom are selected as the master degrees of freedom in each substructure. The performance of the proposed parallel algorithm is demonstrated by applying the algorithm to dynamic analysis of two-dimensional structures.

• Journal of Positioning, Navigation, and Timing
• /
• v.11 no.2
• /
• pp.91-98
• /
• 2022

In the next generation wireless communication system, the beamforming technique based on a massive antenna is one of core technologies for transmitting and receiving huge amounts of data, efficiently and accurately. For highly performed and highly reliable beamforming, it is required to accurately estimate the Angle of Arrival (AOA) for the desired signal incident to an antenna. Employing the massive antenna with a large number of elements, although the accuracy of the AOA estimation is enhanced, its computational complexity is dramatically increased so much that real-time communication is difficult. In order to improve this problem, AOA estimation algorithms based on the massive antenna with the low computational complexity have been actively studied. In this paper, we compute and analyze the computational complexity of the cascade AOA estimation algorithm based on the Flexible Massive Concentric Circular Array (FMCCA). In addition, its computational complexity is compared to conventional AOA estimation techniques such as the Multiple Signal Classification (MUSIC) algorithm with the high resolution and the Only Beamspace MUSIC (OBM) algorithm.

• Proceedings of the KIEE Conference
• /
• 2004.05a
• /
• pp.56-58
• /
• 2004

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm is based on EDS (Euclidean Direction Search) algorithm. Generally LMS algorithm has a much slower rate of convergence, but its low computational complexity and robustness make it a representative method of adaptive beamforming. Although the RLS algorithm is known for its fast convergence to the optimal Wiener solution, it still suffers from high computational complexity and poor performance. The proposed EDS algorithm has a rapid convergence better than LMS algorithm, and has a computational more simple complexity than RLS algorithm. In this paper we compared the efficiency of the EDS algorithm with a standard LMS algorithm.

• Journal of computational fluids engineering
• /
• v.1 no.1
• /
• pp.26-34
• /
• 1996

The performance of the SIMPLE, SIMPLE-C and PISO algorithms for the treatment of the pressure-velocity coupling in fluid flow problems were examined by comparing the computational effort required to obtain the same level of the convergence. Example problems are circular duct and 90-degree bent square-duct. For circular duct case, laminar and turbulent flow were computed. For 90-degree bent square-duct case, laminar flow was simulated by the time-marching method as well as the iterative method. The convergence speed of the other two algorithms are not always superior to SIMPLE algorithm. SIMPLE algorithm is faster than SIMPLE-C algorithm in the simple laminar flow calculations. The application of the PISO algorithm in three dimensional general coordinates is not so effective as in two-dimensional ones. Since computational time of PISO algorithm is increased at each time step(or iterative step) in three dimension, the total convergence speed is not decreased. But PISO algorithm is stable for large time step by using time marching method,.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.444-447
• /
• 2004

A new approach to compute the control moves in Extended Dynamic Matrix Control (EDMC) is presented. In this approach, the number of variables, determined in the inner loop of the control algorithm using iterative methods, is reduced from P , the prediction horizon to M , the control horizon. Since M is usually much smaller than P , this modifies the control algorithm from computational point of view. To justify the modification, the computational requirements are compared to those of the existing EDMC algorithm.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.04b
• /
• pp.466-473
• /
• 2000

Optimality Criteria algorithm based on the derivation of reciprocal approximations has been applied to structural optimization of large-scale structures. However, required computational cost for the serial analysis algorithm of large-scale structures consisting of a large number of degrees of freedom and members is too high to be adopted in the solution process of O.C. algorithm Thus, parallel version of O.C. algorithm on the network of personal computers is presented in this Paper. Parallelism in O.C. algorithm may be classified into two regions such as analysis and optimizer part As the first step of development of parallel algorithm, parallel structural analysis algorithm is developed and used in O.C. algorithm The algorithm is applied to optimal design of a 54-story plane frame structure