• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.78-87
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• 1989

In this paper, a spatio-temporal gradient (STG) method with generalized least square estimation (GLSE) is proposed for the detection of an object motion in an image sequence corrupted by white Gaussian noise. The proposed method is applied to an automatic target tracker using a high speed 16-bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has much better performance over the conventional one with least square estimation (LSE).

• The Journal of Korea Robotics Society
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• v.13 no.1
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• pp.55-62
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• 2018

In this paper, a method for estimation of external force on an end-effector using joint torque sensor is proposed. The method is based on portion of measure torque caused by external force. Due to noise in the torque measurement data from the torque sensor, a recursive least-square estimation algorithm is used to ensure a smoother estimation of the external force data. However it is inevitable to create a delay for the sensor to detect the external force. In order to reduce the delay, modified recursive least-square is proposed. The performance of the proposed estimation method is evaluated in an experiment on a developed six-degree-of-freedom robot. By using NI DAQ device and Labview, the robot control, data acquisition and The experimental results output are processed in real time. By using proposed modified RLS, the delay to estimate the external force with the RLS is reduced by 54.9%. As an experimental result, the difference of the actual external force and the estimated external force is 4.11% with an included angle of $5.04^{\circ}$ while in dynamic state. This result shows that this method allows joint torque sensors to be used instead of commonly used external sensory system such as F/T sensors.

• Journal of Sensor Science and Technology
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• v.26 no.4
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• pp.259-265
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• 2017

Magnetometer calibration must be performed before the use of three-axis magnetometers to ensure the accuracy of orientation estimation. Recently, one of the most popular calibration approaches is the ellipsoid fitting technique due to its high performance in calibration. To date, in fact, performances of the existing ellipsoid fitting methods have been evaluated with full range rotation data. However, in case of the calibration of magnetometers attached to vehicles, ships, and planes, it is very difficult to collect the full range rotation data since their allowable ranges in terms of roll and pitch are limited to small. This constraint may result in serious performance degradation of some ellipsoid fitting algorithms. Therefore, to be practical, this paper proposes a weighted least square-based magnetometer calibration method that is robust in roll-pitch limited conditions. Furthermore, the proposed method is a linear approach and thus is free from the well-known initial value issue in nonlinear approaches. Experimental results show the superiority of the proposed method to other ellipsoid-fitting calibration methods.

• The KIPS Transactions:PartB
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• v.9B no.2
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• pp.223-230
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• 2002

In a speech coding system using excitation source of voiced and unvoiced, it would be involves a distortion of speech waveform in case coexist with a voiced and an unvoiced consonants in a frame. This paper present a new method of TSIUVC (Transition Segment Including Unvoiced Consonant) approximate-synthesis by using Least Mean Square. The TSIUVC extraction is based on a zero crossing rate and IPP (Individual Pitch Pulses) extraction algorithm using residual signal of FIR-STREAK Digital Filter. As a result, This method obtain a high Quality approximation-synthesis waveform by using Least Mean Square. The important thing is that the frequency signals in a maximum error signal can be made with low distortion approximation-synthesis waveform. This method has the capability of being applied to a new speech coding of Voiced/Silence/TSIUVC, speech analysis and speech synthesis.

• Journal of computational fluids engineering
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• v.14 no.4
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• pp.93-100
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• 2009

The gridless (or meshfree) methods, such as MPS, SPH, FPM an so forth, are feasible and robust for the problems with moving boundary and/or complicated boundary shapes, because these methods do not need to generate a grid system. In this study, a gridless solver, which is based on the combination of moving least square interpolations on a cloud of points with point collocation for evaluating the derivatives of governing equations, is presented for two-dimensional unsteady incompressible Navier-Stokes problem in the low Reynolds number. A MAC-type algorithm was adopted and the Poission equation for the pressure was solved successively in the moving least square sense. Some typical problems were solved by the presented solver for the validation and the results obtained were compared with analytic solutions and the numerical results by conventional CFD methods, such as a FVM.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.5
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• pp.89-96
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• 2012

The Falling Weight Deflectormeter has been widely used in evaluating the structural adequacy of pavement structures. The deflections measured from the FWD are capable of estimating the stiffness of pavement layers and measuring the pavement responses in the pavement structure. The objective of paper is to develop the pavement response model using a partial least square regression technique based on the FWD deflection data. The partial least square regression method enables to solve the multicollinearity problem occurred in multiple regression model. It is also found that the pavement response model can be developed using the raw data when a partial least square regression was used.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.4
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• pp.692-700
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• 2017

In this paper, we propose the structural design of Interval Type-2 FCM based RBFNN. Proposed model consists of three modules such as condition, conclusion and inference parts. In the condition part, Interval Type-2 FCM clustering which is extended from FCM clustering is used. In the conclusion part, the parameter coefficients of the consequence part are estimated through LSE(Least Square Estimation) and WLSE(Weighted Least Square Estimation). In the inference part, final model outputs are acquired by fuzzy inference method from linear combination of both polynomial and activation level obtained through Interval Type-2 FCM and acquired activation level through Interval Type-2 FCM. Additionally, The several parameters for the proposed model are identified by using differential evolution. Final model outputs obtained through benchmark data are shown and also compared with other already studied models' performance. The proposed algorithm is performed by using Iris and Vehicle data for pattern classification. For the validation of regression problem modeling performance, modeling experiments are carried out by using MPG and Boston Housing data.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.488-496
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• 2012

In this paper, the scheme for designing optimal beamforming matrix for interference control is proposed. The optimal beamforming matrix is found though linear combination of interference alignment conditions and renewal of linear combination coefficient. The proposed scheme has advantages that the complexity is reduced and there is no multiplying operation in matrix calculations even if proposed scheme has the form similar to that of existing least square based scheme. The simulation results show that proposed scheme has about 4bps/Hz higher gain than existing least square scheme. Also there is no additional multiplying calculation and increase of matrix size when the number of transmit and receive antennas is increased.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.2
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• pp.426-434
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• 2015

In this paper we proposed a dada-aided Doppler estimation method for underwater acoustic communication. The training sequence is non-dedicate, hence it can be designed for Doppler estimation as well as channel equalization. We assume the channel has been equalized and consider only flat-fading channel. First, based on the training symbols the theoretical received sequence is composed. Next the least square principle is applied to build the objective function, which minimizes the error between the composed and the actual received signal. Then an iterative approach is applied to solve the least square problem. The proposed approach involves an outer loop and inner loop, which resolve the channel gain and Doppler coefficient, respectively. The theoretical performance bound, i.e. the Cramer-Rao Lower Bound (CRLB) of estimation is also derived. Computer simulations results show that the proposed algorithm achieves the CRLB in medium to high SNR cases.