• Proceedings of the KOSOMBE Conference
• /
• v.1996 no.05
• /
• pp.31-35
• /
• 1996

This paper presents a real time algorithm for monitoring of the arrythmia of ECG signal. A real time monitoring, following by detecting a QRS complex, is the most important. Using 2-dimensional time-delay coordinates which are reconstructed by the phase portrait plotting special trajectory, we detect QRS complexes. In this study, arrythmias are detected by matching the past standard template with tile present pattern when changing abruptly In order to matching with each other, we propose modified chain coding algorithm which applies vetor table consisting of eight orthonormal code(=binary code) to the phase portraits. This algorithm using logical function increases the weight if exceeding to the threshold determinded by correlation value and the distance from a straight line(y=x). Evaluating the performance of the proposed algorithm, we use standard MIT/BIH database. The results are fellowing, 1) Improve the speed of matching template than that of cross-correlation ever has been used. 2) Because the proposed algorithm is robust to varing fiducial point, it is possible to monitor the ECG signal with irregular RR interval. 3) In spite of baseline wandering owing to the low frequency noise, monitoring performance is not reduced.

• Journal of Digital Convergence
• /
• v.13 no.10
• /
• pp.353-358
• /
• 2015

The Vocabulary Recognition System made by recognizing the standard vocabulary is seen as a decline of recognition when out of the standard or similar words. In this case, reconstructing the system in order to add or extend a range of vocabulary is a way to solve the problem. This paper propose configured Bhattacharyya algorithm standing by speech recognition learning model using the Bayesian methods which reflect parameter estimation upon the model configuration scalability. It is recognized corrected standard model based on a characteristic of the phoneme using the Bayesian methods for parameter estimation of the phoneme's data and Bhattacharyya algorithm for a similar model. By Bhattacharyya algorithm to configure recognition model evaluates a recognition performance. The result of applying the proposed method is showed a recognition rate of 97.3% and a learning curve of 1.2 seconds.

• KEPCO Journal on Electric Power and Energy
• /
• v.3 no.2
• /
• pp.89-97
• /
• 2017

The substation is a critical node in the power network where power is transformed in the power generation, transmission and distribution system. The IEC 61850 is a global standard which proposes efficient substation automation by defining interoperable communication and data modelling techniques. In order to achieve this level of interoperability and automation, the IEC 61850 (Part 6) defines System Configuration description Language (SCL). The SCL is an XML based file format for defining the abstract model of primary and secondary substation equipment, communications systems and also the relationship between them. It enables the interoperable exchange of data during substation engineering by standardizing the description of applications at different stages of the engineering process. To achieve the seamless interoperability, multi-vendor devices are required to adhere completely to the IEC 61850. This paper proposes an efficient algorithm required for verifying the interoperability of multi-vendor devices by checking the adherence of the SCL file to specifications of the standard. Our proposed SCL validation algorithm consists of schema validation and other functionalities including information model validation using UML data model, the Vendor Defined Extension model validation, the User Defined Rule validation and the IED Engineering Table (IET) consistency validation. It also integrates the standard UCAIUG (Utility Communication Architecture International Users Group) Procedure validation for quality assurance testing. Our proposed algorithm is not only flexible and efficient in terms of ensuring interoperable functionality of tested devices, it is also convenient for use by system integrators and test engineers.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.2
• /
• pp.175-181
• /
• 2011

We propose a novel algorithm for measuring the radius of tubes. This proposed algorithm is capable of effectively removing added noise and measuring the radius of tubes within allowable precision. The noise is removed by using a candidate true center that minimizes the standard deviation with respect to the radius. Further, the disconnection in data points resulting from noise removal is solved by using a connection algorithm. The final step of the process is repeated until the value of the standard deviation decreases to a small predefined value. Experiments were performed using circle geometries with added noise and a real tube with complex noise and that is used in the braking units of automobiles. It was concluded that the measurement carried out using the algorithm was accurate within 1.4%, even with 15% added noise.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.25 no.8
• /
• pp.1039-1045
• /
• 2021

In modern society, due to the influence of the 4th industrial revolution, camera sensors and image-based automation systems are being used in various fields, and interest in image and signal processing is increasing. In this paper, we propose a digital filter algorithm for image reconstruction in an impulse noise environment. The proposed algorithm divides the image into eight masks in vertical, horizontal, and diagonal directions based on the local mask set in the image, and compares the standard deviation of each segmentation mask to obtain a reference value. The final output is calculated by applying the weight according to the spatial distance and the weight using the reference value to the local mask. To evaluate the performance of the proposed algorithm, it was simulated with the existing algorithm, and the performance was compared using enlarged images and PSNR.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.3E
• /
• pp.87-96
• /
• 2007

In this paper we propose a new noise reduction algorithm for stationary and nonstationary noisy environments. Our algorithm classifies the speech and noise signal contributions in time-frequency bins, and is not based on a spectral algorithm or a minimum statistics approach. It relies on calculating the ratio of the standard deviation of the noisy power spectrum in time-frequency bins to its normalized time-frequency average. We show that good quality can be achieved for enhancement speech signal by choosing appropriate values for ${\delta}_t\;and\;{\delta}_f$. The proposed method greatly reduces the noise while providing enhanced speech with lower residual noise and somewhat higher mean opinion score (MOS), background intrusiveness (BAK) and signal distortion (SIG) scores than conventional methods.

• Proceedings of the KIEE Conference
• /
• 2004.11c
• /
• pp.602-604
• /
• 2004

A portable electronic tongue(E-Tongue) system using an array of ion-selective electrode(ISE) and personal digital assistants(PDA) for recognizing and analyzing food and drink have been designed. By the employment of PDA, the complex algorithm such as fuzzy c-means algorithm(FCMA) could be used in E-Tongue, FCMA could iteratively solve the cluster centers of pre-determined standard patterns. And the membership between the standard patterns and unknown pattern could be analyzed easily by the present E-Tongue combined with PDA.

• MALSORI
• /
• no.46
• /
• pp.103-115
• /
• 2003

In this paper, we proposed Background Model Set algorithm used in the speaker verification to improve calculating confidence measure(CM) in speech recognition. CM is to display relative likelihood between recognized models and antiphone models. In previous method calculating of CM, we calculated probability and standard deviation using all phonemes in composition of antiphone models. At this process, antiphone CM brought bad recognition result. Also, recognition time increases. In order to solve this problem, we studied about method to reconstitute average and standard deviation using BMS algorithm in CM calculation.

• Journal of information and communication convergence engineering
• /
• v.9 no.5
• /
• pp.487-490
• /
• 2011

This paper presents splitting and merging algorithm based on adaptive thresholding. The algorithm first divides the image into blocks, and then compares each block using the calculated thresholding value. The blocks which are same are merged using the certain threshold value and different blocks are split unless it satisfies the threshold value. When the block has been merged, maximum and minimum block sizes are determined then the average block size is determined. After the average block size is determined the average intensity and standard deviation of average block is calculated. The process of thresholding is applied to binarize the image. Finally, the experimental results show that the proposed method distinguishes clearly the background with text in the document image.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.6
• /
• pp.1867-1873
• /
• 2000

Function approximation from a set of input-output pairs has numerous applications in scientific and engineering areas. Support vector machine (SVM) is a new and very promising classification, regression and function approximation technique developed by Vapnik and his group at AT&TG Bell Laboratories. However, it has failed to establish itself as common machine learning tool. This is partly due to the fact that this is not easy to implement, and its standard implementation requires the use of optimization package for quadratic programming (QP). In this appear we present simple iterative Kernel Adatron (KA) algorithm for function approximation and compare it with standard SVM algorithm using QP.