• Proceedings of the Korean Information Science Society Conference
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• 2000.04a
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• pp.36-38
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• 2000

An optoelectronic database filter chip for high performance database computers and applications is proposed. The proposed device is designed to perform the selection and projection operations of relational database operation on-the-fly in page-parallel manner to increase the overall performance of a database system. The device utilizes CMOS smart pixel array consists of detector and combinational logic circuit to perform the selection and projection operation.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.171-174
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• 2000

This paper proposes a pipelined adaptive filter based on affine projection algorithm with order 2. This filter gives a better convergence performance than that of LMS or NLMS pipeline algorithm and has same latency with the pipeline algorithm based on equivalent transformation. Compared to the critical path of the pipeline NLMS implementation, only 2 additions are increased in that of the proposed implementation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1C
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• pp.82-91
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• 2005

This paper introduces an efficient affine projection algorithm(APA) using iterative hyperplane projection. Among various fast converging adaptation algorithms, APA has been preferred to be employed for various applications due to its inherent effectiveness against the rank deficient problem. However, the amount of complexity of the conventional APA could not be negligible because of the accomplishment of sample matrix inversion(SMI). Moreover, the 'shifting invariance property' usually exploited in single channel case does not hold for the application of space-time decision-directed equalizer(STDE) deployed in single-input-multi-output(SIMO) systems. Thus, it is impossible to utilize the fast adaptation schemes such as fast transversal filter(FlF) having low-complexity. To accomplish such tasks, this paper introduces the low-complexity APA by employing hyperplane projection algorithm, which shows the excellent tracking capability as well as the fast convergence. In order to confirm th validity of the proposed method, its performance is evaluated under wireless SIMO channel in respect to bit error rate(BER) behavior and computational complexity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.163-174
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• 2009

Applying the maximally polyphase decomposition and noble identity to the adaptive filter in subband structure, the conventional fullband affine projection algorithm is translated to the subband affine projection (SAP) algorithm. The Maximally polyphase decomposed SAP (MPDSAP) algorithm is a special version of the SAP algorithm, and its adaptive sub-filters have unity projection dimension. The weight updating formular of the MPDSAP is similar to that of the NLMS algorithm, so it may be more proper algorithm than other AP-type algorithms for many practical applications. This paper presents a new statistical analysis of the MPDSAP algorithm. The analytical model is derived for autoregressive (AR) inputs and the nonunity adaptive gain in the subband structure with the orthonormal analysis filters (OAF), The pre-whitening by the OAF allows the derivation of a simple-analytical model for the MPDSAP with the AR inputs and the nonunity adaptive gain.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.20-25
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• 2011

In subband structure, the fullband AP adaptive filter with P projection dimension can be decomposed P adaptive sub-filters by applying maximally polyphase decomposition and noble identity. Each adaptive sub-filter has a simple weight update formula with the unit projection dimension. This subband decomposition method is one of the most practical solution in the viewpoint of implementation. For utilization in many applications, it is necessary that analysis for the optimum step size of the maximally polyphase decomposed subband AP(MPDSAP) adaptive filter. In this paper, we present an improved analysis model of mean square error and induce the initial optimum step size for the MPDSAP adaptive filter. Computer simulations show that there is a relatively good match between theory and practice for the improved analysis model of MSE and the induced initial optimum step size.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.104-110
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• 2009

In this paper, we suggest a new technique which employ the pipelined architecture for the implementation of the SAP adaptive filter using variable step size. According as SAP adaptive filter is sufficiently decomposed, a simplified SAP adaptive filter can be derived, and the weights of adaptive sub-filters can be updated by a simple formular without a matrix inversion. The convergence speed and the steady state error of the simplified SAP adaptive filter are improved by using variable step size. For practical implementation, the simplified SAP adaptive sub-filters are transformed by the pipeline technique.

• Proceedings of the KIEE Conference
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• 1979.08a
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• pp.158-159
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• 1979

Based on minimum-mean-sqare error criterion, a noise filtering algorithm for the reconstruction of an image function from noisy projection data is suggested. The filter is constructed with a few projection data. This algorithm requires less computational time compared with other noise filtering algorithm.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.5 s.305
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• pp.145-156
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• 2005

In application for acoustic echo cancellation and adaptive equalization, input signal is highly correlated and the long length of adaptive filter is needed. Affine projection algorithms, in these applications, can produce a good convergence performance. However, they have a drawback that is a complex hardware implementation. In this paper, we propose a new subband affine projection algorithm with improved convergence and reduced computational complexity. In addition, we suggest a good approach to implement the proposed method. In this method by applying polyphase decomposition, noble identity and critical decimation to the anne projection algorithm the number of input vectors for decorrelation can be reduced. The weight-updating formula of the proposed method is derived as a simple form that compared with the NLMS(normalized least mean square) algorithm by the reduced projection order The efficiency of the proposed algorithm for a colored input signal was evaluated by using computer simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.4
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• pp.662-674
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• 1997

In order to post process the vector-quantized images employing the theory of projections onto convex sets or the constrained minimization technique, the the projector onto QCS(quantization constraint set) as well as the filter that smoothes the lock boundaries should be investigated theoretically. The basic idea behind the projection onto QCS is to prevent the processed data from diverging from the original quantization region in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in order to reduce the blurring artifacts caused by a filtering operation. However, since the Voronoi regions in the vector quantization are arbitrarilly shaped unless the vector quantization has a structural code book, the implementation of the projection onto QCS is very complicate. This paper mathematically analyzes the projection onto QCS from the viewpoit of minimizing the mean square error. Through the analysis, it has been revealed that the projection onto a subset of the QCS yields lower distortion than the projection onto QCS does. Searching for an optimal constraint set is not easy and the operation of the projector is complicate, since the shape of optimal constraint set is dependent on the statistical characteristics between the filtered and original images. Therefore, we proposed a hyper-cube as a constraint set that enables a simple projection. It sill be also shown that a proper filtering technique followed by the projection onto the hyper-cube can reduce the quantization distortion by theory and experiment.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.2
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• pp.49-58
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• 2012

This paper is on an improved orthogonal projection method which can cancel the acoustic feedback signals in the digital hearing aids. Comparing with the NLMS algorithm which is widely used for simplicity and stability, it shows that this method has the improvement of the convergence performances, and has small computational quantities, for signals with the large auto-correlation as speech signals. This uses the improved orthogonal projection algorithm which reduces the correlation of signals. To verify the convergence characteristics of the proposed algorithm, we simulated about various input signals. The acoustic feedback canceller has a 12-bit resolution with 64-tap adaptive FIR filter. And we compared the results of simulation for this algorithm with the ones for the NLMS algorithm. By these works, it is proved that the feedback canceller adopting the proposed algorithm shows about 3.5dB more high SNR than the NLMS algorithm in the colored input signals.