• Management Science and Financial Engineering
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• v.16 no.2
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• pp.53-65
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• 2010

Despite the overall success of neighbor-based CF methods, there are some fundamental questions about neighbor selection and prediction mechanism including arbitrary similarity, over-fitting interpolation weights, no trust consideration between neighbours, etc. This paper proposes a simple method to compute absolute interpolation weights based on similarity values. In order to supplement the method, two schemes are additionally devised for high-quality neighbour selection and trust metrics based on co-ratings. The former requires that one or more neighbour's similarity should be better than a pre-specified level which is higher than the minimum level. The latter gives higher trust to neighbours that have more co-ratings. Experimental results show that the proposed method outperforms the pure IBCF by about 8% improvement. Furthermore, it can be easily combined with other predictors for achieving better prediction quality.

• MALSORI
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• no.66
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• pp.73-86
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• 2008

Beamforming is one of the spatial filtering techniques which extract only desired signals from noisy environments using microphone arrays. Fixed beamforming is a simple concept and easy to implement. However, it does not show good performance in real noisy conditions. As an adaptive beamforming, Frost algorithm can be a good candidate. It uses the concept of the linearly constrained minimum variance (LCMV) algorithm. The difference between the Frost and the LCMV algorithm is the error correction scheme which is very effective feature in the aspect of performance. In this paper, as quadrature mirror filtering (QMF)-based filterbank is utilized as the pre-processing of the Frost beamformning, the filter length and the learning rate of each band is optimized to improve the performance. The performance is measured by the signal-to-noise ratio (SNR) and the Bark's scale spectral distortion (BSD).

• The Journal of the Acoustical Society of Korea
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• v.22 no.3E
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• pp.110-112
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• 2003

There have been numerous studies on the enhancement of the noisy speech signal. In this paper, we propose a completely new speech enhancement scheme, that is, a filtering of a dissonant frequency (especially F# in each octave of the tempered scale) based on the fundamental frequency which is developed in frequency domain. In order to evaluate the performance of the proposed enhancement scheme, subjective tests (MOS tests) were conducted. The subjective test results indicate that the proposed method provides a significant gain in audible improvement especially for speech contaminated by colored noise and speaking in a husky voice. Therefore when the filter is employed as a pre-filter for speech enhancement, the output speech quality and intelligibility is greatly enhanced.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.2
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• pp.13-17
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• 1985

In this paper, a new pitch extraction method, the area comparison method, is proposed. By the speech production model, the area of the first peak on a pitch interval of speech signals is emphasized. By using the above characteristics, this method have more advantages than the others for pitch extraction. The defective decision caused by an impulsive noise is minimized and the pre-filtering is not necessary for this method, because the intergration of signals takes place in the process.

• International Journal of Ocean System Engineering
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• v.1 no.2
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• pp.89-94
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• 2011

Underwater localization is a crucial capability for reliable operation of various types of underwater vehicles including submarines and underwater robots. However, sea water is almost impermeable to high-frequency electromagnetic waves, and thus absolute position fixes from Global Positioning System (GPS) are not available in the water. The use of acoustic telemetry systems such as Long Baseline (LBL) is a practical option for underwater localization. However, this telemetry network system needs to be pre-deployed and its availability cannot always be assumed. This study focuses on demonstrating the validity of terrain-based localization techniques in a GPS-denied underwater environment. Since terrain-based localization leads to a nonlinear estimation problem, nonlinear filtering methods are required to be employed. The extended Kalman filter (EKF) which is a widely used nonlinear filtering algorithm often shows limited performance under large initial uncertainty. The feasibility of using a particle filter is investigated, which can improve the performance and reliability of the terrain-based localization.

• Carbon letters
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• v.13 no.4
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• pp.248-253
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• 2012

Dielectrophoretic filtering and alignment of single-walled carbon nanotubes (SWCNTs) were tested using deuterium oxide as a solvent. A solution of deuterium oxide-SWCNTs was dropped on top of a silicon chip and an ac electric field was applied between pre-defined electrodes. Deuterium oxide was found to be a better solvent than hydrogen oxide for the dielectrophoresis process with higher efficiency of filtering. This was demonstrated by comparing Raman spectra measured on the initial solution with those measured on the filtered solution. We found that the aligned nanotubes along the electric field were not deposited on the substrate but suspended in solution, forming chain-like structures along the field lines. This so-called pearl chain formation of CNTs was verified by electrical measurements through the aligned tubes. The solution was frozen in liquid nitrogen prior to the electrical measurements to maintain the chain formation. The current-voltage characteristics for the sample demonstrate the existence of conduction channels in the solution, which are associated with the SWCNT chain structures.

• Journal of information and communication convergence engineering
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• v.9 no.1
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• pp.59-63
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• 2011

Conventional noise reduction filtering schemes realize limited improvements of the peak signal-to-noise ratio (PSNR) in the low-level noisy images. The flatness degree and the edge information are effectively used to estimate the noise volume. We propose a noise estimator for reducing noise in the AWGN (additive white gaussian noise) corrupted images using three intermediate image maps (FGM(flatness gray map), FIM(flatness index map), NEM(noise estimate map)). The proposed noise estimator is fed into the conventional noise reduction filters as a pre-processor. The performance of noise reduction is tested in the various AWGN corrupted images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.12A
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• pp.982-990
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• 2009

The IEEE 802.15.4 wireless sensor network is composed of the unique sensor devices to monitor and collect physical or environmental conditions. The interests in a positioning technology, which is one of the environment monitoring technologies, are gradually increased according to the development of the sensor technology and IT infrastructure. Generally, it is difficult for the positioning system using RSSI (Received Signal Strength Indication) based implementation to get accurate position because of obstacles, RF wave's delay and multipath. Therefore, in this paper, we investigate the improved positioning technologies for RSSI-based positioning system. This paper also proposes the enhanced scheme to improve the accuracy of positioning system by applying the Gaussian Filter algorithm, which is widely used for enhancing the performance of image processing system. For the implementation of proposed scheme, we firstly make a look-up tables, which represent the distance between target node and master node and corresponding RSSI value of each target node which are recorded as an average value after investigating the characteristics of attenuation of transmitted signal By applying the pre-determined look-up tables and Gaussian Filtering in the proposed scheme, we analyzed the positioning performance and compared with other conventional RSSI-based positioning algorithms.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.11 s.353
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• pp.8-15
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• 2006

In this paper, we propose the iterative receiver for LDPC-coded OFDMA systems in uplink environments. Applying the Wiener filtering to pilot symbols, an initial channel estimation can be performed effectively. To reduce the complexity of the Wiener filtering, we approximate Wiener filtering coefficients to pre-determined coefficients according to estimated correlation of channel. After an LDPC decoding process, soft symbol derived by extrinsic information of decoder outputs is used to estimate channel. we also derive the error variance of channel estimation and maximum ratio combined results. Using combined results, the channel correlation is re-estimated. Then the proper Wiener filtering coefficients are chosen according to the re-estimated result of the channel correction. Using a computer simulation, we show that the proposed receiver structure has the better performance than the receiver using only pilot symbols.

• Proceedings of the Acoustical Society of Korea Conference
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• 1993.06a
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• pp.259-262
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• 1993

In this paper, a new pitch beginning point detection method by extracting the G-peak, is proposed. By the speech production model, the area of the first peak on a pitch interval of speech signals is emphasized. By using the above characteristics, this method have more advantages than the others for pitch beginning point detection. The defective decision caused by an impulsive noise is minimized and the pre-filtering is not necessary for this method, because the integration of signals takes place in the process.