• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.4
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• pp.667-673
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• 2000

This paper presents the modeling method of nonlinear circuits with lumped elements by using a hybrid Haar -wavelet MRTD/FDTD techniques. To analyze nonlinear circuits with lumped elements, the Haar-wavelet MRTD scheme is applied to the entire structure of interest and the conventional FDTD scheme is locally used to describe the characteristics of the lumped elements. To validate the scheme, microstrip structure with lumped elements and a single diode mixer are simulated.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.6
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• pp.228-234
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• 2002

This paper proposes a real-time application of rationalized Haar transform which is based on the local rationalized Haar transform, local operational matrix and local delay operational matrix. This approach let a general sampling time be used by introducing a scaling factor. In the existing method of orthogonal functions, a major disadvantage is that process signals need to be recorded prior to obtaining their expansions. This paper proposes a novel method of rationalized Haar transform to overcome this shortcoming. And the proposed method is suitable for the analysis of linear systems. The proposed method is expected to the applicable to the adaptive control which demanded to the real-time applications.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.3
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• pp.18-29
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• 2012

Viola-Jones algorithm, a very effective real-time object detection method, uses Haar-like features to constitute weak classifiers. A Haar-like feature is made up of at least two rectangles each of which corresponds to either positive or negative areas and the feature value is computed by subtracting the sum of pixel values in the negative area from that of pixel values in the positive area. Compared to the conventional Haar-like feature which is made up of more than one rectangle, in this paper, we present a couple of new rectangular features whose feature values are computed either by the sum or by the variance of pixel values in a rectangle. By the use of these rectangular features in combination with the conventional Haar-like features, we can select additional features which have been excluded in the conventional Viola-Jones algorithm where every features are the combination of contiguous bright and dark areas of an object. In doing so, we can enhance the performance of object detection without any computational overhead.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.5
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• pp.205-211
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• 2012

By using an adaptive threshold and weight based on the wavelet transform and Haar transform, a novel image enhancement algorithm is proposed. First, a medical image was decomposed with wavelet transform and all high-frequency sub-images were decomposed with Haar transform. Secondly, noise in the frequency domain was reduced by the proposed soft-threshold method. Thirdly, high-frequency coefficients were enhanced by the proposed weight values in different sub-images. Then, the enhanced image was obtained through the inverse Haar transform and wavelet transform. But the pixel range of the enhanced image is narrower than a normal image. Lastly, the image's histogram was stretched by nonlinear histogram equalization. Experiments showed that the proposed method can be not only enhance an image's details but can also preserve its edge features effectively.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.714-724
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• 2006

In this note a method of designing optimal vibration control based on Haar functions to control of bounce and pitch vibrations in engine-body vibration structure is presented. Utilizing properties of Haar functions, a computational method to find optimal vibration control for the engine-body system is developed. It is shown that the optimal state trajectories and optimal vibration control are calculated approximately by solving only algebraic equations instead of solving the Riccati differential equation. Simulation results are included to demonstrate the validity and applicability of the technique.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.4
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• pp.287-292
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• 1987

This paper deals with applications of Haar functions to parameter identification of linear systems. It is first introuduced to a new operational matrix which relates Haar functions and their integrations. The matrix can be used to identify the parameters of unknown linear systems by a least squares estimation. And then, the state equation of given systems is transformed into a computationally convenient algebraic form. This approach provides a more efficient method for the system identification problem.

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2086-2088
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• 2002

This paper deals with an algebraic approach for unknown inputs observer by using Haar functions. In the algebraic UIO(unknown input observer) design procedure, coordinate transformation method is adopted to derive the reduced order dynamic system which is decoupled unknown inputs and Haar function and its integral operational matrix is applied to avoid additional differentiation of system outputs.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.54.4-54
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• 2002

1.Introduction 2. Channel Equalizer Using Adaptive Neural Network 3. Data Modulation and Demodulation Using Haar Transform 4. Binary Signal Transmission Using Haar Transform 5. Conclusion

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.1
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• pp.17-21
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• 2011

This paper presents a real- time detection of on-road succeeding vehicles based on low level edge features and a boosted cascade of Haar-like features. At first, the candidate vehicle location in an image is found by low level horizontal edge and symmetry characteristic of vehicle. Then a boosted cascade of the Haar-like features is applied to the initial hypothesized vehicle location to extract the refined vehicle location. The initial hypothesis generation using simple edge features speeds up the whole detection process and the application of a trained cascade on the hypothesized location increases the accuracy of the detection process. Experimental results on real world road scenario with processing speed of up to 27 frames per second for $720{\times}480$ pixel images are presented.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.835-838
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• 2008

In this paper, we present automatic face detection and tracking which is robustness in rotation and translation. Detecting a face image, we used Haar-like feature, which is fast detect facial image. Also tracking, we applied Lucas-Kanade feature tracker and KLT algorithm, which has robustness for rotated facial image. In experiment result, we confirmed that face detection and tracking which is robustness in rotation and translation.