• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.589-597
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• 2002

In this paper the nonstationary response of accelerating vehicle is firstly obtained by using nonstationary road roughness model in time domain. To get the result of nonstationary response in frequency domain, the maximum entropy method is used for Processing nonstationary response of vehicle in frequency domain. The three-dimensional transient maximum entropy spectrum (MES) of response is given.

• Bulletin of the Korean Chemical Society
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• v.29 no.10
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• pp.2017-2022
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• 2008

Of the experiments to shorten NMR measuring time by sparse sampling, non-uniform sampling (NUS) is advantageous. NUS miminizes systematic errors which arise due to the lack of samplings by randomization. In this study, I report the real-time acquisition of 3D NMR data using NUS and maximum-entropy (MaxEnt) data processing. The real-time acquisition combined with NUS can reduce NMR measuring time much more. Compared with multidimensional decomposition (MDD) method, which was originally suggested by Jaravine and Orekhov (JACS 2006, 13421-13426), MaxEnt is faster at least several times and more suitable for the realtime acquisition. The designed sampling schedule of current study makes all the spectra during acquisition have the comparable resulting resolutions by MaxEnt. Therefore, one can judge the quality of spectra easily by examining the intensities of peaks. I report two cases of 3D experiments as examples with the simulated subdataset from experimental data. In both cases, the spectra having good qualitie for data analysis could be obtained only with 3% of original data. Its corresponding NMR measuring time was 8 minutes for 3D HNCO of ubiquitin.

• Journal of IKEEE
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• v.26 no.2
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• pp.226-231
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• 2022

The concept of information entropy has been widely applied in various fields. Recently, in the field of image processing, many technologies applying the concept of information entropy have been developed. As the importance and demand of computer vision technologies increase in modern industry, real-time processing must be possible in order for image processing technologies to be efficiently applied to modern industries. Extracting the entropy value of an image is difficult to process in real-time due to the complexity of computation in software, and a hardware structure of an image entropy filter capable of real-time processing has never been proposed. In this paper, we propose for the first time a hardware structure of a histogram-based entropy filter that can be processed in real time using a barrel shifter. The proposed hardware was designed using Verilog HDL, and Xilinx's xczu7ev-2ffvc1156 was set as the target device and FPGA was implemented. As a result of logic synthesis using the Xilinx Vivado program, it has a maximum operating frequency of 750.751 MHz in a 4K UHD high-resolution environment, and it processes more than 30 images per second and satisfies the real-time processing standard.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.248-265
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• 2015

In this paper, we propose a maximum entropy-based model, which can mathematically explain the bio-molecular event extraction problem. The proposed model generates an event table, which can represent the relationship between an event trigger and its arguments. The complex sentences with distinctive event structures can be also represented by the event table. Previous approaches intuitively designed a pipeline system, which sequentially performs trigger detection and arguments recognition, and thus, did not clearly explain the relationship between identified triggers and arguments. On the other hand, the proposed model generates an event table that can represent triggers, their arguments, and their relationships. The desired events can be easily extracted from the event table. Experimental results show that the proposed model can cover 91.36% of events in the training dataset and that it can achieve a 50.44% recall in the test dataset by using the event table.

• The Journal of Information Technology
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• v.2 no.2
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• pp.139-144
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• 1999

This thesis is a study on using of entropy information about the additional words in the after processing step to promote an accuracy in speech recognition system. The exsisting ratio of Woodo detective method changes the efficiency of speech recognition system according to speech data and increases the probability of producing error recognition because of similarity of value of Woodo in the additional words. But we could obtain the accurate speech recognition system which heightens discrimination becoming independent of speech data by using of after processing method refusing a candidate which entropy price is lower among words except words we could recognize than entropy Price of each additional word. As a result of this experiment when the false alarm is 20 percent, we could put out the maximum 3.6 percent efficiency of recognition system through this after processing method by entropy more than the method by ratio of Woods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.774-780
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• 2017

This paper proposes an efficient binary arithmetic encoder hardware architecture for CABAC encoding, which is an entropy coding method of HEVC. CABAC is an entropy coding method that is used in HEVC standard. Entropy coding removes statistical redundancy and supports a high compression ratio of images. However, the binary arithmetic encoder causes a delay in real time processing and parallel processing is difficult because of the high dependency between data. The operation of the proposed CABAC BAE hardware structure is to separate the renormalization and process the conventional iterative algorithm in parallel. The new scheme was designed as a four-stage pipeline structure that can reduce critical path optimally. The proposed CABAC BAE hardware architecture was designed with Verilog HDL and implemented in 65nm technology. Its gate count is 8.07K and maximum operating speed of 769MHz. It processes the four bin per clock cycle. Maximum processing speed increased by 26% from existing hardware architectures.

• Computational Structural Engineering
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• v.10 no.4
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• pp.185-193
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• 1997

A major problem of frequency analysis in the field of low-frequencies such as building or construction vibration is the way of signal processing which is appropriate to obtain included frequency content from the finite process to be measured. Therefore, it is the aim of the investigation reported herein to develop the signal processing algorithm which is analyzed without losing the reliability of the measurements in low-frequency domain. To accomplish the research objective, it was analyzed the problems on the way of signal processing in low-frequency domain, and compared the response characteristics of FFT with those of MEM (Maximum Entropy Method) about the low-frequency of vibration. This evaluation of the response characteristics is used in determining appropriate signal processing algorithm into the low-frequency domain.

• Atmosphere
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• v.25 no.3
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• pp.511-520
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• 2015

Existing studies on radar rainfall uncertainties were performed to reduce the uncertainty for each stage by using bias correction during the quantitative radar rainfall estimation process. However, the studies do not provide quantitative comparison with the uncertainties for all stages. Consequently, this study proposes a suitable approach that can quantify the uncertainties at each stage of the quantitative radar rainfall estimation process. First, the new approach can present initial and final uncertainties, increasing or decreasing the uncertainty, and the uncertainty percentage at each stage. Furthermore, Maximum Entropy (ME) was applied to quantify the uncertainty in the entire process. Second, for the uncertainty quantification of radar rainfall estimation at each stage, this study used two quality control algorithms, two rainfall estimation relations, and two bias correction techniques as post-processing and progressed through all stages of the radar rainfall estimation. For the proposed approach, the final uncertainty (ME = 3.81) from the ME of the bias correction stage was the smallest while the uncertainty of the rainfall estimation stage was higher because of the use of an unsuitable relation. Additionally, the ME of the quality control was at 4.28 (112.34%), while that of the rainfall estimation was at 4.53 (118.90%), and that of the bias correction at 3.81 (100%). However, this study also determined that selecting the appropriate method for each stage would gradually reduce the uncertainty at each stage. Finally, the uncertainty due to natural variability was 93.70% of the final uncertainty. Thus, the results indicate that this new approach can contribute significantly to the field of uncertainty estimation and help with estimating more accurate radar rainfall.

• Journal of The Korean Astronomical Society
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• v.27 no.2
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• pp.191-201
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• 1994

We propose to use the entropy of power spectra defined in the frequency domain for the deconvolution of extended images. Spatial correlations requisite for extended sources may be insured by increasing the role of power entropy because the power is just a representation of spatial correlations in the frequency domain. We have derived a semi-analytical solution which is found to severely reduce computing time compared with other iteration schemes. Even though the solution is very similar to the well-known Wiener filter, the regularizingng term in the new expression is so insensitive to the noise characteristics as to assure a stable solution. Applications have been made to the IRAS $60{\mu}m\;and\;100{\mu}m$ images of the dark cloud B34 and the optical CCD image of a solar active region containing a circular sunspot and a small pore.

• Journal of the Korean Institute of Telematics and Electronics
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• v.17 no.1
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• pp.1-9
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• 1980

In this paper several basic techniques for signal processing and analysis are surveyed. Firstly by the intervention of the uncertainty principle, an equality sign may have different degree of precision if non commutable operators are applied. Seconds y maximum entropy estimate and randam process based viewpoint must be enhanced to get rid of the well established and reigning deterministic image of science. Thirdly techniques for the analysis of a signal namely detection. ess]motion and modulation are explained as well as the positive definiteness of a covariance function, Karhunen-Loeve expansion and SVD of an image.