• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.28 no.2C
• /
• pp.181-192
• /
• 2003

Blind equalization of communication channel is important because it does not need training signal, nor does it require a priori channel information. So, we can increase the bandwidth efficiency. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind channel equalizer length mismatch as well as for its simple adaptive implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary decision delay. In this paper, we propose method for fractionally spaced blind equalizer with arbitrary decision delay using one-step forward prediction error filter from second-order statistics of the received signals for SIMO channel. Our algorithm utilizes the forward prediction error as training signal and computes the best decision delay from all possible decision delay. Simulation results are presented to demonstrate the performance of our proposed algorithm.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.7
• /
• pp.618-629
• /
• 2009

The MPEG-4 Audio Lossless Coding (ALS) standard belongs to the family MPEG-4 audio coding standards. In contrast to lossy codecs such as AAC, which merely strive to preserve the subjective audio quality, lossless coding preserves every single bit of the original audio data. The ALS core codec is based on forward-adaptive linear prediction, which combines remarkable compression with low complexity. Additional features include long-term prediction, multichannel coding, and compression of floating-point audio material. This paper describes the basic elements of the ALS codec with a focus on prediction, entropy coding, and related tools and points out the most important applications of this standardized lossless audio format.

• Journal of Broadcast Engineering
• /
• v.14 no.1
• /
• pp.59-69
• /
• 2009

A bi-directional symmetric prediction technique has been developed to improve coding efficiency of B-slice and to reduce the computational complexity required to estimate two motion vectors. On the contrary to the conventional bi-directional mode which encodes both forward and backward motion vectors, it only encodes a single forward motion vector, and the missing backward motion vector is derived in a symmetric way from the forward motion vector using temporal distance between forward/backward reference frames to and from the current B picture. Since the backward motion vector is derived from the forward motion vector, it can halve the computational complexity for motion estimation, and also reduces motion vector data to encode. This technique always derives the backward motion vector from the forward motion vector, however, there are cases when the forward motion vector is better to be derived from the backward motion vector especially in scene changes. In this paper, we generalize the idea of the symmetric coding with forward motion vector coding, and propose a new symmetric coding with backward motion vector coding and adaptive selection between the conventional symmetric mode and the proposed symmetric mode based on rate-distortion optimization.

• International Journal of Computer Science & Network Security
• /
• v.22 no.2
• /
• pp.232-240
• /
• 2022

To fulfill user expectations, the rapid evolution of software techniques and approaches has necessitated reliable and flawless software operations. Aging prediction in the software under operation is becoming a basic and unavoidable requirement for ensuring the systems' availability, reliability, and operations. In this paper, an improved evolutionary computing-driven extreme learning scheme (ECD-ELM) has been suggested for object-oriented software aging prediction. To perform aging prediction, we employed a variety of metrics, including program size, McCube complexity metrics, Halstead metrics, runtime failure event metrics, and some unique aging-related metrics (ARM). In our suggested paradigm, extracting OOP software metrics is done after pre-processing, which includes outlier detection and normalization. This technique improved our proposed system's ability to deal with instances with unbalanced biases and metrics. Further, different dimensional reduction and feature selection algorithms such as principal component analysis (PCA), linear discriminant analysis (LDA), and T-Test analysis have been applied. We have suggested a single hidden layer multi-feed forward neural network (SL-MFNN) based ELM, where an adaptive genetic algorithm (AGA) has been applied to estimate the weight and bias parameters for ELM learning. Unlike the traditional neural networks model, the implementation of GA-based ELM with LDA feature selection has outperformed other aging prediction approaches in terms of prediction accuracy, precision, recall, and F-measure. The results affirm that the implementation of outlier detection, normalization of imbalanced metrics, LDA-based feature selection, and GA-based ELM can be the reliable solution for object-oriented software aging prediction.

• Smart Structures and Systems
• /
• v.14 no.6
• /
• pp.1173-1196
• /
• 2014

Real-time dynamic substructuring tests have been conducted on a cable-deck system. The cable is representative of a full scale cable for a cable-stayed bridge and it interacts with a deck, numerically modelled as a single-degree-of-freedom system. The purpose of exciting the inclined cable at the bottom is to identify its nonlinear dynamics and to mark the stability boundary of the semi-trivial solution. The latter physically corresponds to the point at which the cable starts to have an out-of-plane response when both input and previous response were in-plane. The numerical and the physical parts of the system interact through a transfer system, which is an actuator, and the input signal generated by the numerical model is assumed to interact instantaneously with the system. However, only an ideal system manifests a perfect correspondence between the desired signal and the applied signal. In fact, the transfer system introduces into the desired input signal a delay, which considerably affects the feedback force that, in turn, is processed to generate a new input. The effectiveness of the control algorithm is measured by using the synchronization technique, while the online adaptive forward prediction algorithm is used to compensate for the delay error, which is present in the performed tests. The response of the cable interacting with the deck has been experimentally observed, both in the presence of delay and when delay is compensated for, and it has been compared with the analytical model. The effects of the interface delay in real-time dynamic substructuring tests conducted on the cable-deck system are extensively discussed.

• Proceedings of the Computational Structural Engineering Institute Conference
• /
• 2000.04b
• /
• pp.365-370
• /
• 2000

A sliding mode fuzzy control (SMFC) algorithm is applied to design a controller for a benchmark problem on a wind- excited building. The structure is a 76-story concrete office tower with a height of 306 meters, hence the wind resistance characteristics are very important for the serviceability as well as the safety. A control system with an active tuned mass damper is assumed to be installed on the top floor. Since the structural acceleration is measured only at ,limited number of locations without measurement of the wind force, the structure of the conventional continuous sliding mode control may have the feed-back loop only. So, an adaptive least mean squares (LMS) filter is employed in the SMFC algorithm to generate a fictitious feed-forward loop. The adaptive LMS filter is designed based on the information of the stochastic characteristics of the wind velocity along the structure. A numerical study is carried out. and the performance of the present SMFC with the ,adaptive LMS filter is investigated in comparison with those of' other control, of algorithms such as linear quadratic Gaussian control, frequency domain optimal control, quadratic stability control, continuous sliding mode control, and H/sub ∞///sub μ/, control, which were reported by other researchers. The effectiveness of the adaptive LMS filter is also examined. The results indicate that the present algorithm is very efficient .

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.5
• /
• pp.1109-1122
• /
• 1996

Generally, moving images contain the various components in motions, which reange from a static object and background to a fast moving object. To extract the accurate motion parameters, we must consider the various motions. That requires a wide search egion in motion estimation. The wide search, however, causes a high computational complexity. If we have a few knowledge about the motion direction and magnitude before motion estimation, we can determine the search location and search window size using the already-known information about the motion. In this paper, we present a local adaptive motion estimation approach that predicts a block motion based on spatio-temporal neighborhood blocks and adaptively defines the search location and search window size. This paper presents a technique for reducing computational complexity, while having high accuracy in motion estimation. The proposed algorithm is introduced the forward and backward projection techniques. The search windeo size for a block is adaptively determined by previous motion vectors and prediction errors. Simulations show significant improvements in the qualities of the motion compensated images and in the reduction of the computational complexity.

• Journal of Korea Multimedia Society
• /
• v.14 no.7
• /
• pp.917-923
• /
• 2011

In this paper, a new prediction based embedded compression (EC) codec algorithm for the JPEG2000 encoder system is proposed to reduce excessive memory requirements. The EC technique can reduce the 50 % memory requirement for intermediate low-frequency coefficients during multiple discrete wavelet transform (DWT) stages compared with direct implementation of the DWT engine of this paper. The LOCO-I predictor and MAP are widely used in many lossless picture compression codec. The proposed EC algorithm use these predictor which are very simple but surprisingly effective. The predictive EC scheme adopts a forward adaptive quantization and fixed length coding to encoding the prediction error. Simulation results show that our LOCO-I and MAP based EC codecs present only PSNR degradation of 0.48 and 0.26 dB in average, respectively. The proposed algorithm improves the average PSNR by 1.39 dB compared to the previous work in [9].

• Smart Structures and Systems
• /
• v.13 no.1
• /
• pp.81-98
• /
• 2014

This paper presents the elastic buckling of smart lightweight column structures integrated with a pair of surface piezoelectric layers using artificial intelligence. The finite element modeling of Smart lightweight columns is found using $ANSYS^{(R)}$ software. Then, the first buckling load of the structure is calculated using eigenvalue buckling analysis. To determine the accuracy of the present finite element analysis, a compression study is carried out with literature. Later, parametric studies for length variations, width, and thickness of the elastic core and of the piezoelectric outer layers are performed and the associated buckling load data sets for artificial intelligence are gathered. Finally, the application of soft computing-based methods including artificial neural network (ANN), fuzzy inference system (FIS), and adaptive neuro fuzzy inference system (ANFIS) were carried out. A comparative study is then made between the mentioned soft computing methods and the performance of the models is evaluated using statistic measurements. The comparison of the results reveal that, the ANFIS model with Gaussian membership function provides high accuracy on the prediction of the buckling load in smart lightweight columns, providing better predictions compared to other methods. However, the results obtained from the ANN model using the feed-forward algorithm are also accurate and reliable.

• Journal of the Korean Institute of Telematics and Electronics
• /
• v.26 no.3
• /
• pp.160-166
• /
• 1989

We propose adaptive algorithms computing the coefficients of spatial domain predictors. The method uses the LMS approach to compute the coefficients of the predictors realized by using the TDL(tapped-delay-line) and the ESC (escalator) structures. The predictors to be presented differ from the conventional ones in the sense that the relevant weights are updated such that the sum of the mean squared values of the forward and the backward prediction errors is minimized. Using the coefficients of such spatial domain predictors yields improved linear predictive spatial spectrums. The algorithms are applied to the problems of estimating incident angles of multiple narrow-band signals received by a linear array of sensors. Simulation results demonstrating the performances of the proposed methods are presented.