• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.11
• /
• pp.25-32
• /
• 2007

In this paper, we propose the Group Separation Algorithm for RFID Tag Anti-Collision. We study the RFID Tag anti-collision technique of ALOHA and the anti-collision algorithm of binary search. The existing technique is several problems; the transmitted data rate included of data, the recognition time and energy efficiency. For distinction of all tags, the Group Separation algorithm identify each Tag_ID bit#s sum of bit #1#. In other words, Group Separation algorithm had standard of selection by collision table, the algorithm can reduce unnecessary number of search even than the exisiting algorithm. The Group Separation algorithm had performance test that criterions were reader#s number of repetition and number of transmitted bits for understanding tag. We showed the good performance of Group Separation algorithm better than exisiting algorithm.

• ETRI Journal
• /
• v.36 no.1
• /
• pp.175-178
• /
• 2014

We introduce the Energy-Based Blind Separating (EBS) algorithm for extremely fast separation of mixed speech signals without loss of quality, which is performed in two stages: iterative-form separation and closed-form separation. This algorithm significantly improves the separation speed simply due to incorporating only some specific frequency bins into computations. Simulation results show that, on average, the proposed algorithm is 43 times faster than the independent component analysis (ICA) for speech signals, while preserving the separation quality. Also, it outperforms the fast independent component analysis (FastICA), the joint approximate diagonalization of eigenmatrices (JADE), and the second-order blind identification (SOBI) algorithm in terms of separation quality.

• Smart Structures and Systems
• /
• v.26 no.2
• /
• pp.135-146
• /
• 2020

This paper deals with an application of adaptive blind source separation (BSS) method, equivariant adaptive separation via independence (EASI), and Teager Energy Operator (TEO) for online identification of structural modal parameters. The aim of adaptive BSS methods is recovering a set of independent sources from their unknown linear mixtures in each step when a new sample is received. In the proposed approach, firstly, the EASI method is used to decompose structural responses into independent sources at each instance. Secondly, the TEO based demodulation method with discrete energy separation algorithm (DESA-1) is applied to each independent source, and the instantaneous frequencies and damping ratios are extracted. The DESA-1 method can provide the fast time response and has high resolution so it is suitable for online problems. This paper also compares the performance of DESA-1 algorithm with Hilbert transform (HT) method. Compared to HT method, the DESA-1 method requires smaller amounts of samples to estimate and has a smaller computational complexity and faster adaption due to instantaneous characteristic. Furthermore, due to high resolution of the DESA-1 algorithm, it is very sensitive to noise and outliers. The effectiveness of the proposed approach has been validated using synthetic examples and a benchmark structure.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.1191-1194
• /
• 1998

This paper presents a new computationally efficient adaptive algorithm for blind signal separation, which is able to recover the narrowband source signals in the presence of cochannel interference without a prior knowledge of array manifold. We derive a new blind signal separation algorithm using the Natural gradient 〔1〕from an information-theoretic approach. The resulting algorithm has the Bussgang property which has been widely used in blind equalization 〔12〕. Extensive computer simulation results comfirm the validity and high performance of the proposed algorithm.

• Journal of Korea Multimedia Society
• /
• v.8 no.6
• /
• pp.753-760
• /
• 2005

This paper introduces a variable step-size adaptive algorithm for blind source separation. From the frequency characteristics of mixed input signals, we need to adjust the convergence speed regularly in each frequency bin. This algorithm varies a step-size according to the magnitude of input at each frequency bin. This guarantee of the regular convergence in each frequency bin would become more efficient in separation performances than conventional fixed step-size FDICA. Computer simulation results show the improvement of about 5 dB in signal to interference ratio (SIR) and the better separation quality.

• Earthquakes and Structures
• /
• v.22 no.2
• /
• pp.147-155
• /
• 2022

Regarding the importance of seismic pounding, the available standards and guidelines specify minimum separation distance between adjacent buildings. However, the rules in this field are generally based on some simple assumptions, and the level of confidence is uncertain. This is attributed to the fact that the relative response of adjacent structures is strongly dependent on the frequency content of the applied records and the Eigen frequencies of the adjacent structures as well. Therefore, this research aims at investigating the separation distance of the buildings through a probabilistic-based algorithm. In order to empower the algorithm, the record-to-record uncertainties, are considered by probabilistic approaches; besides, a wide extent of material nonlinear behaviors can be introduced into the structural model by the implementation of the hysteresis Bouc-Wen model. The algorithm is then simplified by the application of the linearization concept and using the response acceleration spectrum. By implementing the proposed algorithm, the separation distance in a specific probability level can be evaluated without the essential need of performing time-consuming dynamic analyses. Accuracy of the proposed method is evaluated using nonlinear dynamic analyses of adjacent structures.

• The Journal of the Acoustical Society of Korea
• /
• v.25 no.4E
• /
• pp.148-153
• /
• 2006

A new normalized MBD algorithm is presented for nonstationary convolutive mixtures and its properties/modifications are discussed in details. The proposed algorithm normalizes the signal spectrum in the frequency domain to provide faster stable convergence and improved separation without whitening effect. Modifications such as nonholonomic constraints and off-diagonal learning to the proposed algorithm are also discussed. Simulation results using a real-world recording confirm superior performanceof the proposed algorithm and its usefulness in real world applications.

• Nuclear Engineering and Technology
• /
• v.55 no.4
• /
• pp.1225-1232
• /
• 2023

The ¹⁸⁰W is the lightest isotope of Tungsten with small abundance ratio. It is slightly radioactive (α decay), with an extremely long half-life. Its separation is possible by non-conventional single withdrawal cascades. The ¹⁸⁰W is used in radioisotopes production and study of metals through gamma-ray spectroscopy. In this paper, single withdrawal cascade model is developed to evaluate multicomponent separation in non-conventional transient cascades, and available experimental results are used for validation. Numerical studies for separation of ¹⁸⁰W in a transient single withdrawal cascade are performed. Parameters affecting the separation and equilibrium time of cascade such as number of stages, cascade arrangements, feed location and flow rate for a fixed number of gas centrifuges (GC) are investigated. The Salp Swarm Algorithm (SSA) as a bio-inspired optimization algorithm is applied as a novel method to minimize the feed consumption to obtain desired concentration in the collection tank. Examining different cascade arrangements, it is observed in arrangements with more stages, the separation is further efficient. Based on the obtained results, with increasing feed flow rate, for fixed product concentration, the cascade equilibrium time decreases. Also, it is shown while the feed location is the farthest stage from the collection tank, the separation and cascade equilibrium time are well-organized. Finally, using SSA optimal parameters of the cascade is calculated, and optimal arrangement to produce 5 gr of ¹⁸⁰W with 90% concentration in the tank, is proposed.

• The Journal of the Acoustical Society of Korea
• /
• v.31 no.5
• /
• pp.317-331
• /
• 2012

In this paper, we develop a multichannel blind source separation algorithm based on a beamspace transform and the multichannel non-negative matrix factorization (NMF) method. The NMF algorithm is a famous algorithm which is used to solve the source separation problems. In this paper, we consider a beamspace-time-frequency domain data model for multichannel NMF method, and enhance the conventional method using a beamspace transform. Our decomposition algorithm is applied to audio source separation, using a dataset from the international Signal Separation Evaluation Campaign 2010 (SiSEC 2010) for evaluation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.93-98
• /
• 1991

An improved and flexible matrix algorithm for solving interlinked separation problems which is based on the homotopy continuation method has been developed. A flexible model of the interlinked stream in standardized matrix form and JACOBIAN generation I algorithm for homotopy continuation are suggested. Also DOF analysis is performed for easy-understanding of equation based simulation of complex column systems. The Algorithm is tested on several problems of interlinked separation processes and some of results are documented.