• Journal of Biomedical Engineering Research
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• v.26 no.4
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• pp.199-205
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• 2005

When recording single-unit responses from neural systems, a common problem is the accurate detection of spikes (action potentials) in the presence of competing unwanted (noise) signals. While some sources of noise can be readily dealt with through filtering or 'template subtraction' techniques, other sources present a more difficult problem. In particular, noise components introduced by power supplies, which contain harmonics of the power-line frequency, can be particularly troublesome in that they can mimic the shape of the desired spikes. Thus, standard 'template subtraction' techniques or notch-filtering approaches are not appropriate. In this study, we propose the use of a novel template-subtraction scheme that involves estimating the power-line noise waveform and using cross-correlation techniques to subtract them from the recordings. This technique requires two key steps: (1) cross-correlation analysis of each recorded waveform extracts a robust representation of the power-line noise waveform and (2) a second level of cross-correlation to successfully subtract that representation from each recorded waveform. This paper describes this algorithm and provides examples of its implementation using actual recorded waveforms that are contaminated with these noise signals. An improvement (reduction) in the noise level is reported, as are suggestions for future implementation of this strategy.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.2
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• pp.154-162
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• 2003

In this paper, Associative Memory with Cellular Neural Networks classifies and recognizes image patterns as an operator applied to image process. CNN processes nonlinear data in real-time like neural networks, and made by cell which communicates with each other directly through its neighbor cells as the Cellular Automata does. It is applied to the optimization problem, associative memory, pattern recognition, and computer vision. Image processing with CNN is appropriate to 2-D images, because each cell which corresponds to each pixel in the image is simultaneously processed in parallel. This paper shows the method for designing the structure of associative memory based on CNN and getting output image by choosing the most appropriate weight pattern among the whole learned weight pattern memories. Each template represents weight values between cells and updates them by learning. Hebbian rule is used for learning template weights and LMS algorithm is used for classification.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.933-934
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• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2007.06a
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• pp.399-400
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• 2007

• Proceedings of the KSR Conference
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• 2008.06a
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• pp.371-377
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• 2008

A design pattern is a general reusable solution to a commonly occurring problem in software design. A design pattern is not a finished design that can be transformed directly into code. It is a description or template for how to solve a problem that can be used in many different situations. Moreover, the name of pattern itself also can be a kind of common language among developers and patterns can be easily imported to various applications demanding similar requirements. In this paper, we present models of CBTC onboard system which follows ERTMS/ETCS specifications and present patterns applied to our system.

• Journal of the Korean Vacuum Society
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• v.16 no.5
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• pp.366-370
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• 2007

Nano-scopic holes which are distributed densely and uniformly were fabricated on $SiO_2$ surface. Self-assembling resists were used to produce a layer of uniformly distributed parallel poly methyl methacrylate (PMMA) cylinders in a polystyrene (PS) matrix. The PMMA cylinders were degraded and removed by acetic acid rinsing. Subsequently, PS nanotemplates were fabricated. The patterned holes of PS template were approximately $8{\sim}30\;nm$ wide, 40 nm deep, and 60 nm apart. The porous PS template was used as a dry etching mask to transfer the pattern of PS template into the silicon oxide thin film during reactive ion etching (RIE) process. The sizes of the patterned holes on $SiO_2$ layer were $9{\sim}33\;nm$. After pattern transfer by RIE, uniformly distributed holes of which size were in the range of $6{\sim}22\;nm$ were fabricated on Si substrate. Sizes of the patterned holes were controllable by PMMA molecular weight.

• The KIPS Transactions:PartB
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• v.13B no.4 s.107
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• pp.377-382
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• 2006

In this paper, two methods based on the use of morphology and pattern matching prior to detect classified defects automatically on the back light unit which is a part of display equipments are proposed. One is the template check method which detects small size defects by using closing and opening method, and the other is the block matching method which detects big size defects by comparing with four regions of uniform blocks. The TC algorithm also can detect defects on the non-uniform pattern of BLU by using revised Otsu method. The proposed method has been implemented on the automatic defect detection system we developed and has been tested image data of BLU captured by the system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.2
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• pp.308-314
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• 2006

A line scan camera is applied to enhance COG(Chip On Glass) inspection accuracy to be measured a few micro unit. The foreign substance detection among various faulty factors has been the most difficult technology in the faulty automatic inspection step since COG pattern is very miniature and complexity. In this paper, we proposed two step area segmentation template matching method to increase matching speed. Futhermore to detect foreign substance(such as dust, scratch) with a few micro unit, the new method using gradient mask and AND operation was proposed. The proposed 2 step template matching method increased 0.3 - 0.4 second matching speed compared with conventional correlation coefficient. Also, the proposed foreign substance applied masks enhanced $5-8\%$ faulty detection rate compared with conventional no mask application method.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.55-58
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• 1997

In this paper, we study a signal processing method which extracts each MUAP(motor unit action potential) from EMG(Electromyogram) interference pattern or clinical diagnostic purposes. First of all, differential digital filtering is selected or eliminating the spike components of the MUAP's from the background noise. And, the algorithm identifies the spikes over the certanin threshold by template matching in frequency domain. After missing or false firing actor is cut off at the IPI(inter pulse interval) histogram, we averages the MUAP waveforms from the raw signal using the identified spikes as triggers, and Finally, measures their amplitudes, durations, and numbers of phases. Specially, We introduce algorithm performed by template matching in the frequency domain. A typical 3-s signal recorded from the biceps brachii muscle using a conventional needle electrode during a isometric contraction is used. Finally, the method decomposed five simultaneous active MUAP's from original EMG signal.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.521-524
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• 2005

This paper proposes a fusion algorithm which merges multiple vein pattern images into a single image, larger than those images. As a preprocessing step of template matching, during the verification of biometric data such as fingerprint image, vein pattern image of hand, etc., the fusion technique is used to make reference image larger than the candidate images in order to enhance the matching performance. In this paper, a new algorithm, called BSA (Boundary Stitching Algorithm) is proposed, in which the boundary rectilinear parts extracted from the candidate images are stitched to the reference image in order to enlarge its matching space. By applying BSA to practical vein pattern verification system, its verification rate was increased by about 10%.