• Title/Summary/Keyword: Linear Time Complexity

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Low Complexity Discrete Hartley Transform Precoded OFDM System over Frequency-Selective Fading Channel

  • Ouyang, Xing;Jin, Jiyu;Jin, Guiyue;Li, Peng
    • ETRI Journal
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    • v.37 no.1
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    • pp.32-42
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    • 2015
  • Orthogonal frequency-division multiplexing (OFDM) suffers from spectral nulls of frequency-selective fading channels. Linear precoded (LP-) OFDM is an effective method that guarantees symbol detectability by spreading the frequency-domain symbols over the whole spectrum. This paper proposes a computationally efficient and low-cost implementation for discrete Hartley transform (DHT) precoded OFDM systems. Compared to conventional DHT-OFDM systems, at the transmitter, both the DHT and the inverse discrete Fourier transform are replaced by a one-level butterfly structure that involves only one addition per symbol to generate the time-domain DHT-OFDM signal. At the receiver, only the DHT is required to recover the distorted signal with a single-tap equalizer in contrast to both the DHT and the DFT in the conventional DHT-OFDM. Theoretical analysis of DHT-OFDM with linear equalizers is presented and confirmed by numerical simulation. It is shown that the proposed DHT-OFDM system achieves similar performance when compared to other LP-OFDMs but exhibits a lower implementation complexity and peak-to-average power ratio.

Linear Feature Simplification Using Wavelets in GIS

  • Liang, Chen;Lee, Chung-Ho;Kim, Jae-Hong;Bae, Hae-Young
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.04b
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    • pp.151-153
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    • 2001
  • Feature Simplification is an essential method for multiple representations of spatial features in GIS. However, spatial features re various, complex and a alrge size. Among spatial features which describe spatial information. linear feature is the msot common. Therefore, an efficient linear feature simplification method is most critical for spatial feature simplification in GIS. This paper propose an original method, by which the problem of linear feature simplification is mapped into the signal processing field. This method avoids conventional geometric computing in existing methods and exploits the advantageous properties of wavelet transform. Experimental results are presented to show that the proposed method outperforms the existing methods and achieves the time complexity of O(n), where n is the number of points of a linear feature. Furthermore, this method is not bound to two-dimension but can be extended to high-dimension space.

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Receivers for Spatially Multiplexed Space-Time Block Coded Systems : Reduced Complexity (시공간블록부호화를 적용한 공간다중화 시스템 수신기 : 복잡도 감소 방안)

  • Hwang Hyeon Chyeol;Shin Seung Hoon;Lee Cheol Jin;Kwak Kyung Sup
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.11A
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    • pp.1244-1252
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    • 2004
  • In this paper, we derive some properties of linear detectors (zero forcing or minimum mean square error) at spatial multiplexing systems with alamouti's space-time block code. Based on the derived properies, this paper proposes low-complexity receivers. Implementing MMSE detector adaptively, the number of weight vectors to be calculated and updated is greatly reduced with the derived properties compared to the conventional methods. In the case of recursive least square algorithm, with the proposed approach computational complexity is reduced to less than the half. We also identify that sorted QR decomposition detector, which reduces the complexity of V-Blast detector, has the same properties for unitary matrix Q and upper triangular matrix R. A complexity reduction of about 50%, for sorted QR decomposition detector, can be achieved by using those properties without the loss of performance.

Linear-Time Korean Morphological Analysis Using an Action-based Local Monotonic Attention Mechanism

  • Hwang, Hyunsun;Lee, Changki
    • ETRI Journal
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    • v.42 no.1
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    • pp.101-107
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    • 2020
  • For Korean language processing, morphological analysis is a critical component that requires extensive work. This morphological analysis can be conducted in an end-to-end manner without requiring a complicated feature design using a sequence-to-sequence model. However, the sequence-to-sequence model has a time complexity of O(n2) for an input length n when using the attention mechanism technique for high performance. In this study, we propose a linear-time Korean morphological analysis model using a local monotonic attention mechanism relying on monotonic alignment, which is a characteristic of Korean morphological analysis. The proposed model indicates an extreme improvement in a single threaded environment and a high morphometric F1-measure even for a hard attention model with the elimination of the attention mechanism formula.

A Reduction Method of Computational Complexity through Adjustment the Non-Uniform Interval in the Vocoder (음성 부호화기에서 불균등 간격조절을 통한 계산량 단축법)

  • Jun, Woo-Jin
    • Proceedings of the KAIS Fall Conference
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    • 2010.05a
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    • pp.277-280
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    • 2010
  • LSP(Line Spectrum Pairs) Parameter is used for speech analysis in vocoders or recognizers since it has advantages of constant spectrum sensitivity, low spectrum distortion and easy linear interpolation. However the method of transforming LPC(Linear Predictive Coding) into LSP is so complex that it takes much time to compute. Among conventional methods, the real root method is considerably simpler than others, but nevertheless, it still suffers from its indeterministic computation time because the root searching is processed sequentially in frequency region. We suggest a method of reducing the LSP transformation time using voice characteristics.

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A Study of stability for solution′s convergence in Karmarkar's & Primal-Dual Interior Algorithm (Karmarkar's & Primal-Dual 내부점 알고리즘의 해의 수렴과정의 안정성에 관한 고찰)

  • 박재현
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.21 no.45
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    • pp.93-100
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    • 1998
  • The researches of Linear Programming are Khachiyan Method, which uses Ellipsoid Method, and Karmarkar, Affine, Path-Following and Interior Point Method which have Polynomial-Time complexity. In this study, Karmarkar Method is more quickly solved as 50 times then Simplex Method for optimal solution. but some special problem is not solved by Karmarkar Method. As a result, the algorithm by APL Language is proved time efficiency and optimal solution in the Primal-Dual interior point algorithm. Furthermore Karmarkar Method and Primal-Dual interior point Method is compared in some examples.

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Advanced Alignment-Based Scheduling with Varying Production Rates for Horizontal Construction Projects

  • Greg Duffy;Asregedew Woldesenbet;David Hyung Seok Jeong;Garold D. Oberlender
    • International conference on construction engineering and project management
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    • 2013.01a
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    • pp.403-411
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    • 2013
  • Horizontal construction projects such as oil and gas pipeline projects typically involve repetitive-work activities with the same crew and equipment from one end of the project to the other. Repetitive scheduling also known as linear scheduling is known to have superior schedule management capabilities specifically for such horizontal construction projects. This study discusses on expanding the capabilities of repetitive scheduling to account for the variance in production rates and visual representation by developing an automated alignment based linear scheduling program for applying temporal and spatial changes in production rates. The study outlines a framework to apply changes in productions rates when and where they will occur along the horizontal alignment of the project and illustrates the complexity of construction through the time-location chart through a new linear scheduling model, Linear Scheduling Model with Varying Production Rates (LSMVPR). The program uses empirically derived production rate equations with appropriate variables as an input at the appropriate time and location based on actual 750 mile natural gas liquids pipeline project starting in Wyoming and terminating in the center of Kansas. The study showed that the changes in production rates due to time and location resulted in a close approximation of the actual progress of work as compared to the planned progress and can be modeled for use in predicting future linear construction projects. LSMVPR allows the scheduler to develop schedule durations based on minimal project information. The model also allows the scheduler to analyze the impact of various routes or start dates for construction and the corresponding impact on the schedule. In addition, the graphical format lets the construction team to visualize the obstacles in the project when and where they occur due to a new feature called the Activity Performance Index (API). This index is used to shade the linear scheduling chart by time and location with the variation in color indicating the variance in predicted production rate from the desired production rate.

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Network traffic prediction model based on linear and nonlinear model combination

  • Lian Lian
    • ETRI Journal
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    • v.46 no.3
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    • pp.461-472
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    • 2024
  • We propose a network traffic prediction model based on linear and nonlinear model combination. Network traffic is modeled by an autoregressive moving average model, and the error between the measured and predicted network traffic values is obtained. Then, an echo state network is used to fit the prediction error with nonlinear components. In addition, an improved slime mold algorithm is proposed for reservoir parameter optimization of the echo state network, further improving the regression performance. The predictions of the linear (autoregressive moving average) and nonlinear (echo state network) models are added to obtain the final prediction. Compared with other prediction models, test results on two network traffic datasets from mobile and fixed networks show that the proposed prediction model has a smaller error and difference measures. In addition, the coefficient of determination and index of agreement is close to 1, indicating a better data fitting performance. Although the proposed prediction model has a slight increase in time complexity for training and prediction compared with some models, it shows practical applicability.

Possibility of Chaotic Motion in the R&D Activities in Korea

  • Loh, Jeunghwee
    • Journal of Information Technology Applications and Management
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    • v.21 no.3
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    • pp.1-17
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    • 2014
  • In this study, various characteristics of R&D related economic variables were studied to analyze complexity of science and technology activities in Korea, as reliance of R&D activities of the private sector is growing by the day. In comparison to other countries, this means that it is likely to be fluctuated by economic conditions. This complexity characteristic signifies that the result of science and technology activities can be greatly different from the anticipated results - depending on the influences from economic conditions and the results of science and technology activities which may be unpredictable. After reviewing the results of 17 variables related to science and technology characteristics of complex systems intended for time-series data - in the total R&D expenditure, and private R&D expenditure, numbers of SCI papers, the existence of chaotic characteristics were. using Lyapunov Exponent, Hurst Exponent, BDS test. This result reveals science and technology activity of the three most important components in Korea which are; heavy dependence on initial condition, the long term memory of time series, and non-linear structure. As stable R&D investment and result are needed in order to maintain steady development of Korea economy, the R&D structure should be less influenced by business cycles and more effective technology development policy for improving human resource development must be set in motion. And to minimize the risk of new technology, the construction of sophisticated technology forecasting system should take into account, for development of R&D system.

A Simple Shortest Path Algorithm for L-visible Polygons

  • Kim, Soo-Hwan
    • Journal of information and communication convergence engineering
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    • v.8 no.1
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    • pp.59-63
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    • 2010
  • The shortest path between two points inside a simple polygon P is a minimum-length path among all paths connecting them which don't pass by the exterior of P. A linear time algorithm for computing the shortest path in a general simple polygon requires triangulating a given polygon as preprocessing. The linear time triangulating is known to very complex to understand and implement it. It is also inefficient in case that the input without very large size is given because its time complexity has a big constant factor. Two points of a polygon P are said to be L-visible from each other if they can be joined by a simple chain of at most two rectilinear line segments contained in P completely. An L-visible polygon P is a polygon such that there is a point from which every point of P is L-visible. We present the customized optimal shortest path algorithm for an L-visible polygon. Our algorithm doesn't require triangulating as preprocessing and consists of simple procedures such as construction of convex hulls and operations for convex polygons, so it is easy to implement and runs very fast in linear time.