• Journal of KIISE:Software and Applications
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• v.32 no.7
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• pp.674-682
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• 2005

This paper proposes classification of multi-spectral satellite image based on fusion of fuzzy G-K (Gustafson-Kessel) algorithm and PCM algorithm. The suggested algorithm establishes the initial cluster centers by selecting training data from each category, and then executes the fuzzy G-K algorithm. PCM algorithm perform using classification result of the fuzzy G-K algorithm. The classification categories are allocated to the corresponding category when the results of classification by fuzzy G-K algorithm and PCM algorithm belong to the same category. If the classification result of two algorithms belongs to the different category, the pixels are allocated by Bayesian maximum likelihood algorithm. Bayesian maximum likelihood algorithm uses the data from the interior of the average intracluster distance. The information of the pixels within the average intracluster distance has a positive normal distribution. It improves classification result by giving a positive effect in Bayesian maximum likelihood algorithm. The proposed method is applied to IKONOS and Landsat TM remote sensing satellite image for the test. As a result, the overall accuracy showed a better outcome than individual Fuzzy G-K algorithm and PCM algorithm or the conventional maximum likelihood classification algorithm.

• KIISE Transactions on Computing Practices
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• v.21 no.1
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• pp.88-93
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• 2015

In modern computer systems, DRAM is commonly used as main memory due to its low read/write latency and high endurance. However, DRAM is volatile memory that requires periodic power supply (i.e., memory refresh) to sustain the data stored in it. On the other hand, PCM is a promising candidate for replacement of DRAM because it is non-volatile memory, which could sustain the stored data without memory refresh. PCM is also available for byte-addressable access and in-place update. However, PCM is unsuitable for using main memory of a computer system because it has two limitations: high read/write latency and low endurance. To take the advantage of both DRAM and PCM, a hybrid main memory, which consists of DRAM and PCM, has been suggested and actively studied. In this paper, we propose a novel page replacement algorithm for hybrid main memory. To cope with the weaknesses of PCM, our scheme focuses on reducing the number of PCM writes in the hybrid main memory. Experimental results shows that our proposed page replacement algorithm reduces the number of PCM writes by up to 80.5% compared with the other page replacement algorithms.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.3
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• pp.169-176
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• 2017

To replace conventional DRAM, many researches have been done on nonvolatile memories. The DRAM&PCM hybrid memory is one of the effective structure because it can utilize an advantage of DRAM and PCM. However, in order to use this characteristics, pages can be replaced frequently between DRAM and PCM. Therefore, PCM still has major problem that has write-limits. Therefore, it needs an effective page management method for exploiting each memory characteristics dynamically and adaptively. So we aim reducing an average access time and write count of PCM by utilizing two locality for an effective page replacement. We proposed a page selection algorithm which is recently requested to write in DRAM and an algorithm witch uses two locality in PCM. According to our simulation, the proposed algorithm for the DRAM&PCM hybrid can reduce the PCM write count by around 22% and the average access time by 31% given the same PCM size, compared with CLOCK-DWF algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.5
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• pp.261-268
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• 2018

Phase Change Memory(PCM) with low power consumption and high integration attracts attention as a next generation nonvolatile memory replacing DRAM. However, there is a problem that PCM has long latency and high energy consumption due to the writing operation. The PCM & DRAM hybrid memory structure is a fruitful structure that can overcome the disadvantages of such PCM. However, the page replacement algorithm is important, because these structures use two memory of different characteristics. The purpose of this document is to effectively manage pages that can be referenced in memory, taking into account the characteristics of DRAM and PCM. In order to manage these pages, this paper proposes an page replacement algorithm based on frequently accessed and recently paged. According to our simulation, the proposed algorithm for the DRAM&PCM hybrid can reduce the energy-delay product by around 10%, compared with Clock-DWF and CLOCK-HM.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.102-107
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• 2009

The Possibilistic C-means(PCM) was proposed to overcome some of the drawbacks associated with the Fuzzy C-means(FCM) such as improved performance for noise data. However, PCM possesses some drawbacks such as sensitivity in initial parameter values and to patterns that have relatively short distances between the prototypes. To overcome these drawbacks, we propose an interval type 2 fuzzy approach to PCM by considering uncertainty in the fuzzy parameter m in the PCM algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.2
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• pp.117-123
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• 2016

In general, PCM (Phase Change Memory) is unsuitable as a main memory because it has limitations: high read/write latency and low endurance. However, the DRAM&PCM hybrid memory with the same level is one of the effective structures for a next generation main memory because it can utilize an advantage of both DRAM and PCM. Therefore, it needs an effective page management method for exploiting each memory characteristics dynamically and adaptively. So we aim reducing an access time and write count of PCM by using an effective page replacement. According to our simulation, the proposed algorithm for the DRAM&PCM hybrid can reduce the PCM access count by around 60% and the PCM write count by 42% given the same PCM size, compared with Clock-DWF algorithm.

• ETRI Journal
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• v.6 no.3
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• pp.9-16
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• 1984

This paper describes $\mu$-law PCM/ADPCM Code Conversion System. The system algorithm is computer-simulated, and with the result of simulation the system is designed by using the Am 2900 family's Bit-Slice Microprocessors which have a high-speed processing power. The ADPCM algorithm is based on Jayant's model and the converting algorithm between $\mu$-law PCM and linear PCM is developed according to the CCITT Recommendation G. 711.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8A
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• pp.598-606
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• 2003

In this paper, we analyze the performance of the PCM cell search algorithm proposed for fast cell search of WCDMA systems. In order to improve both performance and complexity of the cell search algorithm standardized for WCDMA systems the PCM scheme uses a group of the polarization codes produced by a Gold code generator. The PCM scheme only uses one synchronization channel since the polarization codes modulated on P-SCH can replace the RS codes of S-SCH. Thus, the PCM reduces the BS's transmission power since only one synchronization channel can be used, and it can also reduce the complexity of receiver as compared with the conventional one. In this paper, by defining a numerical model, we analyze the performance of the PCM cell search algorithm in terms of detection probability and mean acquisition time. Consequently, we could demonstrate that the PCM cell search algorithm is superior to the standard WCDMA cell search algorithm.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1215-1218
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• 1998

본 논문은 Digital Audio Compression(AC-3) Standard 인 A-52를 기반으로 하였으며 Borland C++3.1 Compiler를 사용하여 AC-3 Decoding Algorithm 구현하였다. Input Stream은 DVD VOB File에서 AC-3 Stream만을 분리하여 사용하며 최종 출력은 16 Bit PCM File이다. AC-3의 Frame구조는 Synchronization Information, Bit Stream Information, Audio Block, Auxiliary Data, Error Check로 구성된다. Aduio Block 은 모두 6개의 Block으로 나뉘어져 있다. BSI와 Side Information을 참조하여 Exponent를 추출하여 Exponent Strategy에 따라 Exponent를 복원한다. 복원된 Exponent 정보를 이용하여 Bit Allocation을 수행하여 각각의 Mantissa에 할당된 Bit수를 계산하고 Stream으로부터 Mantissa를 추출한다. Coupling Parameter를 참조하ㅕ Coupling Channel을 Original Channel로 복원시킨다. Stereo Mode에 대해서는 Rematrixing을 수행한다. Dynamic Range는 Mantissa와 Exponent의 Magnitude를 바꾸는 것으로 선택적으로 사용할 수 있다. Mantissa와 Exponent를 결합하여 Floating Point coefficient로 만든 후 Inverse Transform을 수행하면 PCM Data를 얻을 수 있다. PC에서 듣기 위해서는 Multi Channel을 Stereo나 Mono로 Downmix를 수행한다. 이렇게 만들어진 PCM data는 PCM Data를 재생하는 프로그램으로 재생할 수 있다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.3
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• pp.97-107
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• 1997

Image segmentation is teh important step in image infromation extraction for computer vison sytems. Fuzzy clustering methods have been used extensively in color image segmentation. Most analytic fuzzy clustering approaches are derived from the fuzzy c-means (FCM) algorithm. The FCM algorithm uses th eprobabilistic constraint that the memberships of a data point across classes sum to 1. However, the memberships resulting from the FCM do not always correspond to the intuitive concept of degree of belongingor compatibility. moreover, the FCM algorithm has considerable trouble above under noisy environments in the feature space. Recently, the possibilistic C-mean (PCM) for solving growing for color image segmentation. In the PCM, the membersip values may be interpreted as degrees of possibility of the data points belonging to the classes. So, the problems in the FCM can be solved by the PCM. The clustering results by just PCM are not smoothly bounded, and they often have holes. So, the region growing was used as a postprocessing. In our experiments, we illustrated that the proposed method is reasonable than the FCM in noisy enviironments.