• Title/Summary/Keyword: Computation Complexity

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Low Complexity Noise Predictive Maximum Likelihood Detection Method for High Density Perpendicular Magnetic Recording: (고밀도 수직자기기록을 위한 저복잡도 잡음 예측 최대 유사도 검출 방법)

  • 김성환;이주현;이재진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.6A
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    • pp.562-567
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    • 2002
  • Noise predictive maximum likelihood(NPML) detector embeds noise predictions/ whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This paper shows that NP(1221)ML system through noise predictive PR-equalized signal has less complexity and better performance than high order PR(12321)ML system in high density perpendicular magnetic recording. The simulation results are evaluated using (1) random sequence and (2) run length limited (1,7) sequence, and they are applied to linear channel and nonlinear channel with normalized linear density $1.0{\leq}K_p{\leq}3.0$.

Frame Rate Up-Conversion Considering The Direction and Magnitude of Identical Motion Vectors (동일한 움직임 벡터들의 방향과 크기를 고려한 프레임율 증가기법)

  • Park, Jonggeun;Jeong, Jechang
    • Journal of Broadcast Engineering
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    • v.20 no.6
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    • pp.880-887
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    • 2015
  • In this paper, frame rate up conversion (FRUC) algorithm considering the direction and magnitude of identical motion vectors is proposed. extended bilateral motion estimation (EBME) has higher complexity than bilateral motion estimation (BME). By using average magnitude of motion vector with x and y direction respectively, dynamic frame and static frame are decided. We reduce complexity to decide EBME. also, After we compare the direction and magnitude of identical motion vectors, We reduce complexity to decide motion vector smoothing(MVS). Experimental results show that this proposed algorithm has fast computation and better peak singnal to noise ratio(PSNR) results compared with EBME.

Energy-Efficient Scheduling with Delay Constraints in Time-Varying Uplink Channels

  • Kwon, Ho-Joong;Lee, Byeong-Gi
    • Journal of Communications and Networks
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    • v.10 no.1
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    • pp.28-37
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    • 2008
  • In this paper, we investigate the problem of minimizing the average transmission power of users while guaranteeing the average delay constraints in time-varying uplink channels. We design a scheduler that selects a user for transmission and determines the transmission rate of the selected user based on the channel and backlog information of users. Since it requires prohibitively high computation complexity to determine an optimal scheduler for multi-user systems, we propose a low-complexity scheduling scheme that can achieve near-optimal performance. In this scheme, we reduce the complexity by decomposing the multiuser problem into multiple individual user problems. We arrange the probability of selecting each user such that it can be determined only by the information of the corresponding user and then optimize the transmission rate of each user independently. We solve the user problem by using a dynamic programming approach and analyze the upper and lower bounds of average transmission power and average delay, respectively. In addition, we investigate the effects of the user selection algorithm on the performance for different channel models. We show that a channel-adaptive user selection algorithm can improve the energy efficiency under uncorrelated channels but the gain is obtainable only for loose delay requirements in the case of correlated channels. Based on this, we propose a user selection algorithm that adapts itself to both the channel condition and the backlog level, which turns out to be energy-efficient over wide range of delay requirement regardless of the channel model.

Motion Vector Resolution Decision Algorithm based on Neural Network for Fast VVC Encoding (고속 VVC 부호화를 위한 신경망 기반 움직임 벡터 해상도 결정 알고리즘)

  • Baek, Han-gyul;Park, Sang-hyo
    • Journal of Broadcast Engineering
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    • v.26 no.5
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    • pp.652-655
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    • 2021
  • Among various inter prediction techniques of Versatile Video Coding (VVC), adaptive motion vector resolution (AMVR) technology has been adopted. However, for AMVR, various MVs should be tested per each coding unit, which needs a computation of rate-distortion cost and results in an increase in encoding complexity. Therefore, in order to reduce the encoding complexity of AMVR, it is necessary to effectively find an optimal AMVR mode. In this paper, we propose a lightweight neural network-based AMVR decision algorithm based on more diverse datasets.

A Linguistic Study on the Sentence Problems in 2015 revised Elementary Mathematics Textbooks (초등수학 교과서 문장제의 언어적 분석)

  • Kim, Young A;Kim, Sung Joon
    • East Asian mathematical journal
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    • v.35 no.2
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    • pp.115-139
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    • 2019
  • In problem solving education, sentence problems are a tool for comprehensive evaluation of mathematical ability. The sentence problems refer to the problem expressed in sentence form rather than simply a numerical representation of mathematical problems. In order to solve sentence problems with a mixture of mathematical terms and general language, problem-solving ability including the ability to understand the meaning of sentences as well as the mathematical computation ability is required. Therefore, it is important to analyze syntactic elements from the linguistic aspects in sentence problems. The purpose of this study is to investigate the complexity of sentence problems in the length of sentences and the grammatical complexity of the sentences in the depth of the sentences by analyzing the 51 sentence problems presented in the $4^{th}$ grade mathematics textbook(2015 revised curriculum). As a result, it was confirmed that it is necessary to examine the length and depth of the sentence more carefully in the teaching and learning of sentence problems. Especially in elementary mathematics, the sentence problems requires a linguistic understanding of the sentence, and therefore it is necessary to consider syntactic elements in the process of developing and teaching sentence problems in mathematics textbook.

Improved Blind Cyclic Algorithm for Detection of Orthogonal Space-Time Block Codes

  • Le, Minh-Tuan;Pham, Van-Su;Mai, Linh;Yoon, Gi-Wan
    • Journal of information and communication convergence engineering
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    • v.4 no.4
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    • pp.136-140
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    • 2006
  • In this paper, we consider the detection of orthogonal space-time block codes (OSTBCs) without channel state information (CSI) at the receiver. Based on the conventional blind cyclic decoder, we propose an enhanced blind cyclic decoder which has higher system performance than the conventional one. Furthermore, the proposed decoder offers low complexity since it does not require the computation of singular value decomposition.

Blind Multi-User Detector Using Code-Constrained Minimum Variance Method (코드 제한 최소 분산 방법을 이용한 블라인드 다중 사용자 검파기)

  • 임상훈;정형성이충용윤대희
    • Proceedings of the IEEK Conference
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    • 1998.10a
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    • pp.215-218
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    • 1998
  • This paper proposes a blind multi-user detector using Code-Constrained Minimum Variance (CCMV) method which directly detects the DS-CDMA signals in a multipath fading channel without estimating the channels. This algorithm reduces the complexity of computation by making a small size data matrix with the order of the channel length. Advantageously it requires to know the spreading code and the time delay of only the desired user.

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Fast motion estimation algorithm with adjustable searching area (적응 탐색 영역을 가지는 고속 움직임 추정 알고리즘)

  • 정성규;정차근;조경록
    • Proceedings of the IEEK Conference
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    • 1998.06a
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    • pp.757-760
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    • 1998
  • A new motion estimation algorithm with lower computational complexity and good image quality when compared to the FBMA will be presented in this paper. In the proposed method, by considering the relation between neighboring blocks, the searching area in the algorithm is adjustable according to mean absolute difference of the block. By the computer simulation the computation amount of the proposed than that of the FBMA and the good result of the PSNR can be attained.

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Speaker Identification using Phonetic GMM (음소별 GMM을 이용한 화자식별)

  • Kwon Sukbong;Kim Hoi-Rin
    • Proceedings of the KSPS conference
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    • 2003.10a
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    • pp.185-188
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    • 2003
  • In this paper, we construct phonetic GMM for text-independent speaker identification system. The basic idea is to combine of the advantages of baseline GMM and HMM. GMM is more proper for text-independent speaker identification system. In text-dependent system, HMM do work better. Phonetic GMM represents more sophistgate text-dependent speaker model based on text-independent speaker model. In speaker identification system, phonetic GMM using HMM-based speaker-independent phoneme recognition results in better performance than baseline GMM. In addition to the method, N-best recognition algorithm used to decrease the computation complexity and to be applicable to new speakers.

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Fast Super-Resolution Algorithm Based on Dictionary Size Reduction Using k-Means Clustering

  • Jeong, Shin-Cheol;Song, Byung-Cheol
    • ETRI Journal
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    • v.32 no.4
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    • pp.596-602
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    • 2010
  • This paper proposes a computationally efficient learning-based super-resolution algorithm using k-means clustering. Conventional learning-based super-resolution requires a huge dictionary for reliable performance, which brings about a tremendous memory cost as well as a burdensome matching computation. In order to overcome this problem, the proposed algorithm significantly reduces the size of the trained dictionary by properly clustering similar patches at the learning phase. Experimental results show that the proposed algorithm provides superior visual quality to the conventional algorithms, while needing much less computational complexity.