• Journal of Advanced Information Technology and Convergence
• /
• v.10 no.1
• /
• pp.1-14
• /
• 2020

Antenna selection is a method to enhance the performance of spatial multiplexing multiple-input multiple-output (MIMO) systems, which can achieve the diversity order of the full MIMO systems. Although various selection criteria have been studied in the literature, they should be adjusted to the detection operation implemented at the receiver. In this paper, antenna selection methods that optimize the post-processing signal-to-noise ratio (SNR) and eigenvalue are considered for the lattice reduction (LR)-based receiver. To develop a complexity-efficient antenna selection algorithm, the incremental selection strategy is adopted. Moreover, for improvement of performance, an additional iterative selection method is presented in combination with an incremental strategy.

• Journal of Internet Computing and Services
• /
• v.13 no.2
• /
• pp.13-20
• /
• 2012

SLM (Selected Mapping) is an efficient PAPR (Peak-to-Average Power Ratio) reduction scheme without transmitted signal distortion in OFDM (Orthogonal Frequency Division Multiplexing) systems. However, enormous IFFTs (Inverse Fast Fourier Transforms) are needed to generate sufficient candidate OFDM signals, which cause the SLM to become quite complex. In this paper, we propose a new SLM scheme that replaces the IFFT operations with a conversion of the first candidate OFDM signal. The proposed scheme significantly reduces computational complexity, while it shows almost the same PAPR performance as the conventional SLM scheme.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.4
• /
• pp.551-558
• /
• 2014

Baseline drift reduction and removal of power line noises in electrocardiogram are often necessary to avoid the distortions in extracting the fiducial features. With this aim, the multirate digital filtering algorithm is suggested to design and implement Finite Impulse Response or Infinite Impulse Response Filter by changing the sampling rate with omitting or interpolating intermediate ECG data. After the experimental simulations performed, we can conclude the fact that we can suppress the baseline wander and power line disturbances in ECG signal with reducing the computational complexities in which we do not keep the original and high sampling frequency.

• Proceedings of the IEEK Conference
• /
• 2005.11a
• /
• pp.93-96
• /
• 2005

We propose a computationally efficient sphere decoding (SD) algorithm with smart radius control (SRC). As a baseline algorithm for SD, we consider the modified Schnorr-Euchner (SE) algorithm [1] (hereafter, called as the MSE algorithm). In principle, the radius after zero-forcing decision feedback equalization (ZF-DFE) estimation can be reduced further if we select a new lattice vector closer to the received signal vector than the lattice vector corresponding to the ZF-DFE estimate does. In our case, we obtain such a better lattice vector by performing a sequence of alternating one-dimensional searches, starting from the ZF-DFE estimate. We then develop a novel SRC algorithm that adopts adaptively the additional radius reduction process according to the estimated signal-to-noise-power ratio (SNR) after ZF-DFE estimation. In addition, we analyze the effect of detection ordering on the complexity for SD. Column-norm ordering of the channel matrix and optimal ordering [1] are considered here. From our analyses, we see that SRC can reduce greatly the complexity for SD and the degree of complexity reduction gets significant as the SNR decreases, irrespective of detection ordering schemes used.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.4
• /
• pp.817-822
• /
• 2011

This paper first proposes the speech recognition algorithm by detection of the speech and noise sections at each frame using a neural network training by back-propagation algorithm, then proposes the spectral subtraction method which removes the noises at each frame according to detection of the speech and noise sections. In this experiment, the performance of the proposed recognition system was evaluated based on the recognition rate using various speeches that are degraded by white noise and car noise. Moreover, experimental results of the noise reduction by the spectral subtraction method demonstrate using the speech and noise sections detecting by the speech recognition algorithm at each frame. Based on measuring signal-to-noise ratio, experiments confirm that the proposed algorithm is effective for the speech by corrupted the noise using signal-to-noise ratio.

• Journal of the korean Society of Automotive Engineers
• /
• v.14 no.5
• /
• pp.95-106
• /
• 1992

Active control of acoustic noise is an application area of adaptive digital signal processing with increasingly interest along the last year. This work studies the implementation of the multichannel LMS filter and the application of this algorithm for the reduction of the noise inside a vechicle cabin using a number of 'secondary sources' drived by adaptive filtering of a reference noise source. Firstly, we propose the use of an adaptive method for the time-varient optimal convergence factor. Secondly, we propose the use of adaptive delayed inverse model to estimate the elastic-acoustic transfer function presented in vechicle cabin. The original, primary source is often periodic, with a known fundamental frequency. A suitably filtered reference signal can thus be used to drive the secondary sources. An algorithm is presented for adapting the coefficients of an FIR filter feeding such a secondary source in such a way as to minimize the output of a suitably placed microphone. In this algorithm, the coefficients of adaptive filter driving an array of secondary sources can be adapted to minimize the sum of the squares of the outputs of a number of error microphones. The multichannel LMS algorithm displays that such an algorithm is considered suitable to used for the global suppression of noise in vehicle cabin.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.5
• /
• pp.2197-2204
• /
• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• The Transactions of the Korean Institute of Power Electronics
• /
• v.8 no.1
• /
• pp.89-97
• /
• 2003

High frequency common mode voltage produced by PWM inverter fed Induction motor is a major cause of conducted EMI, creation motor ground currents, bearing currents and other harmful products. The zero switching states of inverter control invoke large in comparison with the non-zero switching state of Inverter control. We proposed a common mode voltage reduction method based on sinusoidal PWM technique. PWM signal are generated by comparing respective sinusoidal reference signal with three triangular carrier wave displaced of 120$^{\circ}$. Simulation and experimenta1 result show that common mode voltages in the proposed PWM technique are reduced by approximate 66% more than conventional FWM technique.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.1
• /
• pp.29-36
• /
• 2004

Generally, wavelet coefficients can be classified into two categories: large coefficients with much signal information and small coefficients with little signal component. This statistical characteristic of wavelet coefficient is approximated to Gaussian mixture model and efficiently applied to noise reduction. In this paper, we propose an image denoising method using mixture modeling of wavelet coefficients. Binary mask value is generated by proper threshold which classifies wavelet coefficients into two categories. Information of binary mask value is used to remove image noise. We also develope an enhancement method of mask value using morphological filter, and apply it to image denoising for improvement of the proposed method. Simulation results shows the proposed method have better PSNRs than those of the state of art denoising methods.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.2
• /
• pp.95-102
• /
• 2001

Fuzzy system is capable of uniformly approximating any nonlinear function over compact input space. The applications of fuzzy system, however, have been primarily limited by the need for large number of fuzzy rules, in particular, for the high-order nonlinear system. In this paper, we propose the reconstruction methods of fuzzy systems, parallel type and cascade, based on the decomposition of some classes of high-order nonlinear functions. Using the both types appropriately, we can reduce the number of fuzzy rules geometrically. It can be applied to the fuzzy system that has an online adaptive structure. Two examples of adaptive fuzzy sliding mode control are shown in the computer simulations to verify the validity of the proposed algorithm.