Jin-Hoon Kim
Korea Advanced Institute of Science and Technology · Engineering
About the Lab
Professor Jin-Hoon Kim's research lab specializes in adaptive signal processing, intelligent control systems, and bio-inspired machine learning, with a strong focus on developing robust and efficient algorithms for real-world applications. The lab explores advanced adaptive filtering techniques—such as variable step-size sign subband algorithms and multi-channel active noise control—for enhanced performance in noisy or uncertain environments. It also investigates biologically inspired neural network architectures that emulate complex neuronal dynamics using multi-input activation functions, aiming to improve learning efficiency and generalization. Additionally, the lab contributes to materials science through the development and characterization of functional coatings, particularly Cu-based bulk metallic glasses, for improved corrosion resistance and performance under thermal stress.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15A new variable step‐size sign subband adaptive filter (VSS‐SSAF), not requiring any a priori information, is proposed by minimising the ℓ 1 ‐norm of the subband a posteriori error under a box‐constraint on the step‐size. In addition, an efficient numerical procedure for updating its VSS is introduced to solve the non‐differentiable convex problem. The proposed algorithm provides comparable or better convergence performance, when compared with the recent VSS‐SSAF (minimising the mean‐squares devi
A closed‐form design of a two‐dimensional (2D) finite impulse response (FIR) filter with circular, rectangular, fan or quadrant‐fan shapes in the passband region is presented. The computationally efficient 2D FIR filter can be implemented using frequency transformation and sampling‐kernel‐based interpolation instead of an optimisation algorithm. When compared with the existing method, the proposed method reduces 90% of multiplications for filtering. Several design examples are demonstrated to ve
For continuous state space applications, a novel method of Q-learning is proposed, where the method incorporates a region-based reward assignment being used to solve a structural credit assignment problem and a convex clustering approach to find a region with the same reward attribution property. Our learning method can estimate a current Q-value of an arbitrarily given state by using effect functions, and has the ability to learn its actions similar to that of Q-learning. Thus, our method enabl
Neurons in the brain are complex machines with distinct functional compartments that interact nonlinearly. In contrast, neurons in artificial neural networks abstract away this complexity, typically down to a scalar activation function of a weighted sum of inputs. Here we emulate more biologically realistic neurons by learning canonical activation functions with two input arguments, analogous to basal and apical dendrites. We use a network-in-network architecture where each neuron is modeled as
In multi-channel active noise control (ANC) systems, online secondary-path modeling (OSPM) using the auxiliary noise signal is often applied. However, the additive noise signal may contribute to the residual output noise. In this paper, the conventional noise power scheduling, utilized for single-channel ANC with OSPM, is further extended to multi-channel ANC. Simulation results demonstrate that the proposed approach yields better ANC performance, compared with conventional multi-channel ANC met
Abstract In this study, Cu-based bulk metallic glass coatings were deposited by atmospheric plasma spraying with different hydrogen flow rates. The crystallization and oxidation of the coatings is assessed along with corrosion resistance. As thermal energy in the plasma jet increases, the melting fraction and oxidation of particles in the coating increases as does porosity. All of these factors have an effect on the corrosion resistance of Cu-based bulk metallic glass coatings and their relative
A monolayer of L1 <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sub> FePt nanoparticles was fabricated on a polymer film by introducing a Au seed layer prior to the Fe-Pt deposition on the polyimide film. The particle size distribution was tightened from 5.1plusmn1.8 nm to 3.8plusmn1.1 nm by introducing the Au seeds to induce a preferential nucleation of the deposited metal on the preexisting Au particles. Deposition and annealing was repeated
Research Areas
Dive deeper into Jin-Hoon Kim's research on Nubint
Open this lab's papers in the app to read with AI, summarize, and cite in your writing.