• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.8
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• pp.1226-1237
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• 1993

For data transmission over strictly band-limited non-ideal channels, different types of filters with arbitrary responses are needed. In this paper. we proposed two efficient techniques for the design of such FIR filters whose response is specified in either the time or the frequency domain. In particular when a fractionally-spaced structure is used for the transceiver, these filters can be efficiently designed by making use of characteristics of oversampling. By using a minimum mean-squared error criterion, we design a fractionally-spaced FIR filter whose frequency response can be controlled without affecting the output error. With proper specification of the shape of the additive noise signals, for example, the design results in a receiver filter that can perform compromise equalization as well as phase splitting filtering for QAM demodulation. The second method ad-dresses the design of an FIR filter whose desired response can be arbitrarily specified in the frequency domain. For optimum design, we use an iterative optimization technique based on a weighted least mean square algorithm. A new adaptation algorithm for updating the weighting function is proposed for fast and stable convergence. It is shown that these two independent methods can be efficiently combined together for more complex applications.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.4
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• pp.675-683
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• 1992

Mapping and navigation system based on certainty grids for an autonomous mobile robt operating in unknown and unstructured environment is described. The system uses sonar range data to build a map of robot's surroundings. The range data from sonar sensor are integrated into a probability map that is composed of two dimensional grids which contain the probabilities of being occupied by the objects in the environment. A Bayesian model is used to estimate the uncertainty of the sensor information and to update the existing probability map with new range data. The resulting two dimensional map is used for path planning and navigation. In this paper, the Bayesian updating model which was successfully simulated in our earlier work is implemented on a mobile robot and is shown to be valid in the real world through experiment. This paper also proposes a technique for reducing for reducing specular reflection problem of sonar system which seriousely deteriorates the map quality, and a new path planning method based on weighted distance, which enables the robot to efficiently navigate in an unknown area.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4
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• pp.261-268
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• 2003

Conventional acoustic echo cancellers using ES algorithm have simple structure and fast convergence speed compared with those using NLMS algorithm, but they are very weak to external noise because ES algorithm updates the adaptive filter taps based on average energy reduction rate of room impulse response in specific acoustical condition. To solve this problem, in this paper, a new update algorithm for acoustic echo canceller with stepsize matrix generator is proposed. A set of stepsizes is determined based on residual error energy which is estimated by two moving average operators, and applied to the echo canceller in matrix from, resulting in improved convergence speed. Simulations in various noise condition show that the proposed algorithm improves the robustness of acoustic echo canceller to external noise.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.21-27
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• 2002

Inspection and shape measurement of three-dimensional objects are widely needed in industries for quality monitoring and control. A number of visual or optical technologies have been successfully applied to measure three-dimensional surfaces. However, those conventional visual or optical methods have inherent shortcomings such as occlusion and variant surface reflection. X-ray vision system can be a good solution to these conventional problems, since we can extract the volume information including both the surface geometry and the inner structure of any objects. In the x-ray system, the surface condition of an object, whether it is lambertian or specular, does not affect the inherent characteristics of its x-ray images. In this paper, we propose a three-dimensional x-ray imaging method to reconstruct a three dimensional structure of an object out of two dimensional x-ray image sets. To achieve this by the proposed method, two or more x-ray images projected from different views are needed. Once these images are acquired, the simultaneous algebraic reconstruction technique(SART) is usually utilized. Since the existing SART algorithms have several shortcomings such as low performance in convergence and different convergence within the reconstruction volume of interest, an advanced SART algorithm named as USART(uniform SART) is proposed to avoid such shortcomings and improve the reconstruction performance. Because, each voxel within the volume is equally weighted to update instantaneous value of its internal density, it can achieve uniform convergence property of the reconstructed volume. The algorithm is simulated on various shapes of objects such as a pyramid, a hemisphere and a BGA model. Based on simulation results the performance of the proposed method is compared with that of the conventional SART method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.08a
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• pp.73-76
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• 2008

We present a area-based method for stereo matching using varying weights. A central problem in a area-based stereo matching is different result from selecting a window size. Most of the previous window-based methods iteratively update windows. However, the iterative methods very sensitive the initial disparity estimation and are computationally expensive. To resolve this problem, we proposed a new function to assign weights to pixels using features. To begin with, we extract features in a given stereo images based on edge. We adjust the weights of the pixels in a given window based on correlation of the stereo images. Then, we match pixels in a given window between the reference and target images of a stereo pair. The proposed method is compared to existing matching strategies using both synthetic and real images. The experimental results show the improved accuracy of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3738-3760
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• 2022

Due to increasing spectrum demand for new wireless devices applications, cooperative spectrum sensing (CSS) paradigm is the most promising solution to alleviate the spectrum shortage problem. However, in the interweave cognitive radio (CR) system, the inherent nature of CSS opens a hole to Byzantine attack, thereby resulting in a significant drop of the CSS security and efficiency. In view of this, a weighted differential sequential single symbol (WD3S) algorithm based on MATLAB platform is developed to accurately identify malicious users (MUs) and benefit useful sensing information from their malicious reports in this paper. In order to achieve this, a dynamic Byzantine attack model is proposed to describe malicious behaviors for MUs in an interweave CR system. On the basis of this, a method of data transmission consistency verification is formulated to evaluate the global decision's correctness and update the trust value (TrV) of secondary users (SUs), thereby accurately identifying MUs. Then, we innovatively reuse malicious sensing information from MUs by the weight allocation scheme. In addition, considering a high spectrum usage of primary network, a sequential and differential reporting way based on a single symbol is also proposed in the process of the sensing information submission. Finally, under various Byzantine attack types, we provide in-depth simulations to demonstrate the efficiency and security of the proposed WD3S.

• Journal of the Korea Society for Simulation
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• v.19 no.2
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• pp.91-98
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• 2010

Conventional path-finding has focused on finding short collision-free paths. However, as computer games become more sophisticated, it is required to take tactical information like ambush points or lines of enemy sight into account. One way to make this information have an effect on path-finding is to represent a heuristic function of a search algorithm as a weighted sum of tactics. In this paper we consider the problem of learning heuristic to optimize path-finding based on given tactical information. What is meant by learning is to produce a good weight vector for a heuristic function. Training examples for learning are given by a game level-designer and will be compared with search results in every search level to update weights. This paper proposes a learning algorithm integrated with search for tactical path-finding. The perceptron-like method for updating weights is described and a simulation tool for implementing these is presented. A level-designer can mark desired paths according to characters' properties in the heuristic learning tool and then it uses them as training examples to learn weights and shows traces of paths changing along with weight learning.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.75-77
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• 2021

A variety of search engines are currently in use. The search engine supports the retrieval of data required by users through three stages: crawling, index generation, and output of search results based on meta-tag information. However, a large number of documents obtained by searching for keywords are often unrelated or scarce. Because of these problems, it takes time and effort to grasp the content from the search results and classify the accuracy. The index of search engines is updated periodically, but the criteria for weighted values and update periods are different from one search engine to another. Therefore, this paper uses the LSTM model, which extracts the relationship between keywords entered by the user and documents instead of the existing search engine, and improves the relationship between keywords and documents by entering keywords that the user wants to find.

• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.21-29
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• 2008

The High Level Architecture(HLA) specifies a framework for interoperation between heterogeneous simulators, and Run-Time Infrastructure(RTI) is a implementation of the HLA Interface Specification. The Data Distribution Management(DDM) services, one category of IEEE 1516 HLA/RTI management services, control filters for data transmission and reception of data volume among simulators. In this paper, we propose design concept of DDM and show its implementation for light-weighted RTI. The design concept of DDM is to minimize total amount of message that each federate and a federation process generate using the rate of RTI service execution. The design of our proposed DDM follows that a data transfer mechanism is differently applied as the rate of RTI service execution. A federate usually publishes or subscribes data when it starts. The federate constantly updates the data and modifies associated regions while it continues to advance its simulation time. Therefore, the proposed DDM design provides fast update or region modification in exchange of complex publish and subscribe services. We describe how to process the proposed DDM in IEEE 1516 HLA/RTI and experiment variable scenarios while modifying region, changing overlap ratio, and increasing data volume.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.4
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• pp.29-39
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• 2017

Various electronic warfare situations drive the need to develop an integrated electronic warfare simulator that can perform electronic warfare modeling and simulation on radar threats. In this paper, we analyze the components of a simulation system to reversely model the radar threats that emit electromagnetic signals based on the parameters of the electronic information, and propose a method to gradually maintain the reverse extrapolation model of RF threats. In the experiment, we will evaluate the effectiveness of the incremental model update and also assess the integration method of reverse extrapolation models. The individual model of RF threats are constructed by using decision tree, naive Bayesian classifier, artificial neural network, and clustering algorithms through Euclidean distance and cosine similarity measurement, respectively. Experimental results show that the accuracy of reverse extrapolation models improves, while the size of the threat sample increases. In addition, we use voting, weighted voting, and the Dempster-Shafer algorithm to integrate the results of the five different models of RF threats. As a result, the final decision of reverse extrapolation through the Dempster-Shafer algorithm shows the best performance in its accuracy.