Young-Seok Choi

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We propose a novel affine projection algorithm (APA) that updates the weights intermittently. While the conventional APA updates the weights at each time instant, the proposed APA performs an intermittent update of the weights through dynamically adjusting the update interval. The adjustment of the update interval is accomplished by comparing the squared(More)
We present a novel normalized least mean square (NLMS) algorithm with robust regularization. The proposed algorithm dynamically updates the regularization parameter that is fixed in the conventional epsi-NLMS algorithms. By exploiting the gradient descent direction we derive a computationally efficient and robust update scheme for the regularization(More)
We propose an adaptive regularized affine projection algorithm (AR-APA) with a regularization matrix. Instead of the conventional fixed and weighted identity matrix for regularization, the proposed AR-APA incorporates a nonidentity regularization matrix which is dynamically updated. The adaptation of the regularization matrix is accomplished by the(More)
We present a novel normalized subband adaptive filter (NSAF) which dynamically selects subband filters in order to reduce computational complexity while maintaining convergence performance of conventional NSAF. The selection operation is performed to achieve the largest decrease between the successive mean square deviations at every iteration. As a result,(More)
We propose a family of novel affine projection algorithms (APA) with adaptive regularization matrix. Conventional regularized APA (R-APA) uses a fixed and weighted identity matrix for regularization. The proposed algorithms incorporate a non-identity regularization matrix which is also dynamically updated. The matrix adaptation is based on the normalized(More)
An equation-error adaptive infinite-impulse response (IIR) filtering method has slow convergence rate when the input signal is correlated. To overcome this problem, we present a new equation-error adaptive IIR filtering method based on data reuse. We also provide the corresponding debiasing solution for the proposed algorithm. Experimental result(More)
We propose two new affine projection algorithms (APA) with variable regularization parameter. The proposed algorithms dynamically update the regularization parameter that is fixed in the conventional regularized APA (R-APA) using a gradient descent based approach. By introducing the normalized gradient, the proposed algorithms give birth to an efficient and(More)
An opportunistic human pathogen, Pseudomonas aeruginosa, contains the major catalase KatA, which is required to cope with oxidative and osmotic stresses. As an attempt to uncover the H2O2-dependent regulatory mechanism delineating katA gene expression, four prototrophic H2O2-sensitive mutants were isolated from about 1,500 TnphoA mutant clones of P.(More)
The multi-host pathogen, Pseudomonas aeruginosa, possesses an extraordinary versatility which makes it capable of surviving the adverse conditions provided by environmental, host, and, presumably, competing microbial factors in its natural habitats. Here, we investigated the P. aeruginosa-Bacillus subtilis interaction in laboratory conditions and found that(More)