• Journal of Advanced Marine Engineering and Technology
• /
• v.32 no.5
• /
• pp.768-774
• /
• 2008

In many areas of speech signal processing such as automatic speech recognition and packet based voice communication technique, VAD (voice activity detection) plays an important role in the performance of the overall system. In this paper, we present a new feature parameter for VAD which is the product of energy of the signal and the difference of two types of entropies. For this end, we first define a Mel filter-bank based entropy and calculate its difference from the conventional entropy in frequency domain. The difference is then multiplied by the spectral energy of the signal to yield the final feature parameter which we call PEED (product of energy and entropy difference). Through experiments. we could verify that the proposed VAD parameter is more efficient than the conventional spectral entropy based parameter in various SNRs and noisy environments.

• Advances in nano research
• /
• v.12 no.3
• /
• pp.263-279
• /
• 2022

In this research, the physical education training quality was investigated using the entropy model to compute variance associated with a random value (a strong tool). The entropy and undefined estimation principles are used to extract the greatest entropy of information dependent on the index system. In the study of tennis motion tracking from a dynamic viewpoint, such stages are utilized to improve the perception of the players' achievement (Lv et al. 2020). Six female tennis players served on the right side (50 cm from the T point). The initial flat serve from T point was the movement under consideration, and the entropy was utilized to weigh all indications. As a result, a multi-index measurement vector is stabilized, followed by the confidence level to determine the structural plane establishment range. As a result, the use of the unascertained measuring technique of information entropy showed an excellent approach to assessing athlete performance more accurately than traditional ways, enabling coaches and athletes to enhance their movements successfully.

• Journal of the Korea Society of Computer and Information
• /
• v.21 no.5
• /
• pp.31-40
• /
• 2016

In this paper, we analyse the characteristics of the edge image and propose a new entropy coding optimized to the compression of the edge image. The pixel values of the edge image have the Gaussian distribution around '0', and most of the pixel values are '0'. By using this analysis, the Zero Block technique is utilized in spatial domain. And the Intra Prediction Mode of the edge image is similar to the mode of the surrounding blocks or likely to be the Planar Mode or the Horizontal Mode. In this paper, we make use of the MPM technique that produces the Intra Prediction Mode with high probability modes. By utilizing the above properties, we design a new entropy coding method that is suitable for edge image and perform the compression. In case the existing compression techniques are applied to edge image, compression ratio is low and the algorithm is complicated as more than necessity and the running time is very long, because those techniques are based on the natural images. However, the compression ratio and the running time of the proposed technique is high and very short, respectively, because the proposed algorithm is optimized to the compression of the edge image. Experimental results indicate that the proposed algorithm provides better visual and PSNR performance up to 11 times than the JPEG.

• Proceedings of the KSRS Conference
• /
• 2008.10a
• /
• pp.29-32
• /
• 2008

In this paper, we propose one unsupervised classification technique using the degree of polarization (DoP) and the co-polarized phase-difference (CPD) statistics, instead of the entropy and alpha. It is shown that the DoP is closely related to the entropy, and the CPD to the alpha. The DoP explains the feature how much the effect of multiple reflections is contained. Hence, the DoP could be used as an important factor for classifying classes. The CPD can also be computed from the measured Mueller matrix elements. For the smooth surface scattering, the CPD is about $0^{\circ}$, and for dihedral-type scattering, the CPD is about $180^{\circ}$. A DoP-CPD diagram with appropriate boundaries between six different classes is developed based on the SAR image. The classification results are compared with the existing Entropy-alpha diagram as well as the IPL-AirSAR polarimetric data. The technique may have capability to classify an SAR image into six major classes; a bare surface, a village, a crown-layer short vegetation canopy, a trunk-layer short vegetation canopy, a crown-layer forest, and a trunk-dominated forest. Based on the DoP and CPD analysis, a simple three-component decomposition technique was also proposed.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.27 no.1
• /
• pp.69-75
• /
• 2003

In this study, his technique was applied to a GDI spray in order to investigate the mixture distribution. In addition, the homogeneity degree and diffusion effect according to ambient temperature in the high pressure chamber were analyzed by using an entropy analysis method. From this experiment, we could find that entropy analysis is very effective method for the analysis of mixture formation, and the entropy values increase with the progress of uniformity in diffusion Process. we tried to provide the fundamental data for parameter which effects on the spray macroscopic characteristics with mixture ratio of diesel and gasoline. In addition, the mixture formation was analyzed by using entropy analysis. The entropy analysis is based on the concept of statistical entropy, and it identifies the degree of homogeneity in the fuel concentration. From the entropy analysis results we could find that the direct diffusion phenomena is a dominant factor in the formation of a homogeneous mixture at downstream of GDI spray especially in vaporizing conditions. As to increasing ambient temperature and increasing gasoline rate, the entropy intensity using the statistic thermodynamics method is increased because evaporation rate is higher gasoline than diesel.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.7 no.10
• /
• pp.2479-2496
• /
• 2013

Increasing demand for Full High-Definition (FHD) video and Ultra High-Definition (UHD) video services has led to active research on high speed video processing. Widespread deployment of multi-core systems has accelerated studies on high resolution video processing based on parallelization of multimedia software. Even if parallelization of a specific decoding step may improve decoding performance partially, such partial parallelization may not result in sufficient performance improvement. Particularly, entropy decoding has often been considered separately from other decoding steps since the entropy decoding step could not be parallelized easily. In this paper, we propose a parallelization technique called Integrated Multi-Threaded Parallelization (IMTP) which takes parallelization of the entropy decoding step, with other decoding steps, into consideration in an integrated fashion. We used the Simultaneous Multi-Threading (SMT) technique with appropriate thread scheduling techniques to achieve the best performance for the entire decoding step. The speedup of the proposed IMTP method is up to 3.35 times faster with respect to the entire decoding time over a conventional decoding technique for H.264/AVC videos.

• Journal of the Chungcheong Mathematical Society
• /
• v.28 no.1
• /
• pp.109-117
• /
• 2015

We consider the relative entropy for two R-CGMY processes, which are CGMY processes with Y equal to 1, to choose an equivalent martingale measure (EMM) when the underlying asset of a derivative follows a R-CGMY process in the financial market. Since the R-CGMY process leads to an incomplete market, we have to use a proper technique to choose an EMM among a variety of EMMs. In this paper, we derive the closed form expression of the relative entropy for R-CGMY processes.

• Smart Structures and Systems
• /
• v.11 no.3
• /
• pp.299-314
• /
• 2013

This paper presents a nonlinear time series analysis technique for evaluating machine defect severity, based on the Recurrence Plot (RP) entropy. The RP entropy is calculated from the probability distribution of the diagonal line length in the recurrence plot, which graphically depicts a system's dynamics and provides a global picture of the autocorrelation in a time series over all available time-scales. Results of experimental studies conducted on a spindle-bearing test bed have demonstrated that, as the working condition of the bearing deteriorates due to the initiation and/or progression of structural damages, the frequency information contained in the vibration signal becomes increasingly complex, leading to the increase of the RP entropy. As a result, RP entropy can serve as an effective indicator for defect severity assessment of rolling bearings.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.17 no.12 s.115
• /
• pp.1249-1258
• /
• 2006

Two-dimensional(2-D) radar images, namely, ISAR images from a maneuvering target include unwanted phase errors due to the target's motion. These phase errors make ISAR images to be blurred. The ISAR autofocus technique is required in order to remove these unwanted phase errors. Unless those unwanted phase errors produced by the target's motion are removed prior to target identification, we cannot expect a reliable target identification performance. In this paper, we use the entropy-based ISAR autofocus technique which consists of two steps: range alignment and phase adjustment. We analyze a relationship between the number of sampling point and a image quality in a range alignment algorithm and also analyze a technique for reducing computation time of the SSA(Stage-by-Stage Approachng) algorithm in a phase adjustment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.8 no.4
• /
• pp.333-337
• /
• 2002

A content-based image retrieval method using color, texture, and shape features is proposed in this paper. A region segmentation technique using PIM(Picture Information Measure) entropy is used for similarity indexing. For segmentation, a color image is first transformed to a gray image and it is divided into n$\times$n non-overlapping blocks. Entropy using PIM is obtained from each block. Adequate variance to perform good segmentation of images in the database is obtained heuristically. As variance increases up to some bound, objects within the image can be easily segmented from the background. Therefore, variance is a good indication for adequate image segmentation. For high variance image, the image is segmented into two regions-high and low entropy regions. In high entropy region, hue-saturation-intensity and canny edge histograms are used for image similarity calculation. For image having lower variance is well represented by global texture information. Experiments show that the proposed method displayed similar images at the average of 4th rank for top-10 retrieval case.