• Journal of Communications and Networks
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• v.11 no.2
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• pp.166-174
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• 2009

In this paper, a distributed power and end-to-end rate control algorithm is proposed in the presence of licensed users. By Lagrangian duality theory, the optimal power and rate control solution is given for the unlicensed users while satisfying the interference temperature limits to licensed users. It is obtained that transmitting with either 0 or the maximum node power is the optimal scheme. The synchronous and asynchronous distributed algorithms are proposed to be implemented at the nodes and links. The convergence of the proposed algorithms are proved. Finally, further discussion on the utility-based fairness is provided for the proposed algorithms. Numerical results show that the proposed algorithm can limit the interference to licensed user under a predefined threshold.

• ETRI Journal
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• v.35 no.4
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• pp.697-705
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• 2013

Emerging trends in the area of digital very large scale integration (VLSI) signal processing can lead to a reduction in the cost of the cochlear implant. Digital signal processing algorithms are repetitively used in speech processors for filtering and encoding operations. The critical paths in these algorithms limit the performance of the speech processors. These algorithms must be transformed to accommodate processors designed to be high speed and have less area and low power. This can be realized by basing the design of the auditory filter banks for the processors on digital VLSI signal processing concepts. By applying a folding algorithm to the second-order digital gammatone filter (GTF), the number of multipliers is reduced from five to one and the number of adders is reduced from three to one, without changing the characteristics of the filter. Folded second-order filter sections are cascaded with three similar structures to realize the eighth-order digital GTF whose response is a close match to the human cochlea response. The silicon area is reduced from twenty to four multipliers and from twelve to four adders by using the folding architecture.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1001-1007
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• 2020

In recent years, machine learning algorithms are continuously being used and expanded in various fields, such as facial recognition, signal processing, personal authentication, and stock prediction. In particular, various algorithms, such as deep learning, reinforcement learning, and Q-learning, are continuously being improved. Among these algorithms, the expansion of deep learning is rapidly changing. Nevertheless, machine learning algorithms have not yet been applied in several fields, such as personal authentication technology. This technology is an essential tool in the digital information era, walking recognition technology as promising biometrics, and technology for solving state-space problems. Therefore, algorithm technologies of deep learning, reinforcement learning, and Q-learning, which are typical machine learning algorithms in various fields, such as agricultural technology, personal authentication, wireless network, game, biometric recognition, and image recognition, are being improved and expanded in this paper.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.9-14
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• 2006

Galileo is the European Global Navigation Satellite System, under civilian control, and consists on a constellation of medium Earth orbit satellites and its associated ground infrastructure. Galileo will provide to their users highly accurate global positioning services and their associated integrity information. The elements in charge of the computation of Galileo navigation and integrity information are the OSPF (Orbit Synchronization Processing Facility) and IPF (Integrity Processing Facility), within the Galileo Ground Mission Segment (GMS). Navigation algorithms play a key role in the provision of the Galileo Mission, since they are responsible for computing the essential information the users need to calculate their position: the satellite ephemeris and clock offsets. Such information is generated in the Galileo Ground Mission Segment and broadcast by the satellites within the navigation signal, together with the expected a-priori accuracy (SISA: Signal-In-Space Accuracy), which is the parameter that in fault-free conditions makes the overbounding the predicted ephemeris and clock model errors for the Worst User Location. In parallel, the integrity algorithms of the GMS are responsible of providing a real-time monitoring of the satellite status with timely alarm messages in case of failures. The accuracy of the integrity monitoring system is characterized by the SISMA (Signal In Space Monitoring Accuracy), which is also broadcast to the users through the integrity message.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.178-183
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• 2006

As a lot of researches on the speech signal processing are performed due to the recent rapid development of the information-communication technology. the pitch period is used as an important element to various speech signal application fields such as the speech recognition. speaker identification. speech analysis. or speech synthesis. A variety of algorithms for the time and the frequency domains related with such pitch period detection have been suggested. One of the pitch detection algorithms for the time domain. AMDF (average magnitude difference function) uses distance between two valley points as the calculated pitch period. However, it has a problem that the algorithm becomes complex in selecting the valley points for the pitch period detection. Therefore, in this paper we proposed the modified AMDF(M-AMDF) algorithm which recognizes the entire minimum valley points as the pitch period of the speech signal by using the rotation transform of AMDF. In addition, a threshold is set to the beginning portion of speech so that it can be used as the selection criteria for the pitch period. Moreover the proposed algorithm is compared with the conventional ones by means of the simulation, and presents better properties than others.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.201-206
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• 2006

Genetic Algorithms have been known to provide near optimal solutions for various optimization problems in engineering. In this paper, we study the effect of gene order in genetic algorithms on the defining length of the schema with high fitness values. Its effect on the performance of genetic algorithms was also analyzed through two well known problems. A few gene reordering methods were proposed for graph partitioning and knapsack problems. Experimental results showed that genetic algorithms with gene reordering could find solutions of better qualities compared to the ones without gene reordering. It is very important to find proper reordering method for a given problem to improve the performance of genetic algorithms.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.128-132
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• 2011

Least mean square adaptive algorithms have played important role in radar, sonar, speech processing, and mobile communication. In mobile communication area, the convergence rate of a LMS algorithm is quite important. However, LMS algorithms have slow and non-uniform convergence rate problem For overcoming these shortcomings, various variable step LMS adaptive algorithms have been studied in recent years. Most of these recent LMS algorithms have used complex variable step methods to get a rapid convergence. But complex variable step methods need a high computational complexity. Therefore, the main merits such as the simplicity and the robustness in a LMS algorithm can be eroded. The proposed deterministic variable step LMS algorithm is based upon a simple deterministic function for the step update so that the simplicity of the proposed algorithm is obtained and the fast convergence is still maintainable.

• Structural Engineering and Mechanics
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• v.71 no.1
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• pp.57-63
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• 2019

During the last two decades, much joint research regarding vibration based methods has been done, leading to developing various algorithms and techniques. These algorithms and techniques can be divided into modal methods and signal methods. Although modal methods have been widely used for health monitoring and damage detection, signal methods due to higher efficiency have received considerable attention in various fields, including aerospace, mechanical and civil engineering. Signal-based methods are derived directly from the recorded responses through signal processing algorithms to detect damage. According to different signal processing techniques, signal-based methods can be divided into three categories including time domain methods, frequency domain methods, and time-frequency domain methods. The frequency domain methods are well-known and interest in using them has increased in recent years. To determine dynamic behaviours, to identify systems and to detect damages of bridges, different methods and algorithms have been proposed by researchers. In this study, a new algorithm to detect seismic damage in the bridge's piers is suggested. To evaluate the algorithm, an analytical model of a bridge with simple spans is used. Based on the algorithm, before and after damage, the bridge is excited by a sine force, and the piers' responses are measured. The dynamic specifications of the bridge are extracted by Power Spectral Density function. In addition, the Least Square Method is used to detect damage in the bridge's piers. The results indicate that the proposed algorithm can identify the seismic damage effectively. The algorithm is output-only method and measuring the excitation force is not needed. Moreover, the proposed approach does not need numerical models.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.78-85
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• 1996

The set of admissible time-variations in the input signal can be separated into two categories : slow parameter changes and large parameter changes which occur infrequently. A common approach used in the tracking of slowly time-varying parameters is the exponential recursive least-squares(RLS) algorithm. There have been a variety of research works on the error analysis of the exponential RLS algorithm for the slowly time-varying parameters. In this paper, the focus has been given to the error analysis of exponential RLS algorithms for the input data with abrupt property changes. The voiced speech signal is chosen as the principal application. In order to analyze the error performance of the exponential RLS algorithm, deterministic properties of the exponential RLS algorithms is first analyzed for the case of abrupt parameter changes, the impulsive input(or error variance) synchronous to the abrupt change of parameter vectors actually enhances the convergence of the exponential RLS algorithm. The analysis has also been verified through simulations on the synthetic speech signal.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.2
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• pp.65-72
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• 2006

In digital signal processing, the polyphase decomposition of signal has been often used in the implementation of multirate system. Especially, in the design of digital filter and so forth the method in very useful to improve the performance of various algorithms because it provides the multi-channel for paralled processing. Generally, the polyphase-decomposed signals tend to expand the frequency band by including more high frequencies than original signal from decimation for down sampling. This property brings about the significant limitation in the structure or the performance of digital polyphase signal processing system. In this paper we theoretically propose a perfect band compression and reconstruction method for polyphase component signals, then experimentally show its effectiveness through Matlab simulation.