• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.1
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• pp.364-370
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• 2011

The Hilbert transform performs a role to transform band pass signals into low pass signals in wireless communication systems. The operation of Hilbert transform is based on a convolution process which is required adding and multiplying calculations. When the Hilbert transform is designed and hardware-implemented at gate level, the adding and multiplying operation requires a high power consumption and a occupation of wide area on a chip. So the results of adding and multiplying operation cause to degrade the performance of implemented system. In this paper, the new Hilbert transformer is proposed, which has a low hardware complexity by application of MAG(Minimum Adder Graph) algorithm. The proposed Hilbert transformer was simulated in ISE environment of Xilinx and showed the reduction of hardware complexity comparing with the number of gate in the conventional Hilbert transformer.

• Journal of the Chungcheong Mathematical Society
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• v.26 no.2
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• pp.323-342
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• 2013

Let $C[0,t]$ denote the function space of all real-valued continuous paths on $[0,t]$. Define $Xn:C[0,t]{\rightarrow}\mathbb{R}^{n+1}$ and $X_{n+1}:C[0,t]{\rightarrow}\mathbb{R}^{n+2}$ by $X_n(x)=(x(t_0),x(t_1),{\cdots},x(t_n))$ and $X_{n+1}(x)=(x(t_0),x(t_1),{\cdots},x(t_n),x(t_{n+1}))$, where $0=t_0$ < $t_1$ < ${\cdots}$ < $t_n$ < $t_{n+1}=t$. In the present paper, using simple formulas for the conditional expectations with the conditioning functions $X_n$ and $X_{n+1}$, we evaluate the $L_p(1{\leq}p{\leq}{\infty})$-analytic conditional Fourier-Feynman transforms and the conditional convolution products of the functions which have the form $${\int}_{L_2[0,t]}{{\exp}\{i(v,x)\}d{\sigma}(v)}{{\int}_{\mathbb{R}^r}}\;{\exp}\{i{\sum_{j=1}^{r}z_j(v_j,x)\}dp(z_1,{\cdots},z_r)$$ for $x{\in}C[0,t]$, where $\{v_1,{\cdots},v_r\}$ is an orthonormal subset of $L_2[0,t]$ and ${\sigma}$ and ${\rho}$ are the complex Borel measures of bounded variations on $L_2[0,t]$ and $\mathbb{R}^r$, respectively. We then investigate the inverse transforms of the function with their relationships and finally prove that the analytic conditional Fourier-Feynman transforms of the conditional convolution products for the functions, can be expressed in terms of the products of the conditional Fourier-Feynman transforms of each function.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.91-97
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• 2007

Points of sharp variations in signals are the most important factors when analyzing the features of signals. And in the image, edges include diverse information such as the locations, shape and material. There have been a variety of researches on edge detections, among them, methods based on convolution in the spatial domain have been most popular. However at the early stage of the method, if the noise and many kinds of edges exist in the image, it is not easy to separate edges selectively from corrupted images by noise. In meantime, the wavelet transform for multiscale edge detection is being applied widely to analyze the properties of images in various fields. In this paper, we suggest a robust wavelet-based method, which selectively detects line-edge elements from images in the presence of noise.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.374-385
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• 2019

This paper presents an optimal implementation of a Daubechies-based pipelined discrete wavelet packet transform (DWPT) processor using finite impulse response (FIR) filter banks. The feed-forward pipelined (FFP) architecture is exploited for implementation of the DWPT on the field-programmable gate array (FPGA). The proposed DWPT is based on an efficient transpose form structure, thereby reducing its computational complexity by half of the system. Moreover, the efficiency of the design is further improved by using a canonical-signed digit-based binary expression (CSDBE) and advanced functional sharing (AFS) methods. In this work, the AFS technique is proposed to optimize the convolution of FIR filter banks for DWPT decomposition, which reduces the hardware resource utilization by not requiring any embedded digital signal processing (DSP) blocks. The proposed AFS and CSDBE-based DWPT system is embedded on the Virtex-7 FPGA board for testing. The proposed design is implemented as an intellectual property (IP) logic core that can easily be integrated into DSP systems for sub-band analysis. The achieved results conclude that the proposed method is very efficient in improving hardware resource utilization while maintaining accuracy of the result of DWPT.

• Journal of the Korean Institute of Telematics and Electronics
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• v.14 no.6
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• pp.26-30
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• 1977

Redundancies in the Calculation of DFT and FFT are analized and new algorithms are proposed which are capable of reducing the machine time by a considerable amount. New extensions of T.D C.F. and T.D.F.T. are given for the discrete case which permit a deeper insights for the techniques of digital signal Proessing i. e. Discrete Fourier Transform, Convolution Sum and Correlation sequences.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.3
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• pp.291-297
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• 2012

Conventional Fourier analysis can give only limited information about the dynamic characteristics of nonstationary signals. Instead, time-frequency analysis is widely used to investigate the nonstationary signal in detail. Several time-frequency analysis methods are compared for a typical acoustic emission burst generated during the impact between a ferrite ceramic and aluminum plate. This AE burst is inherently nonstationary and random containing many frequency contents, which leads to severe interference between cross terms in bilinear convolution type distributions. The smoothing and reassignment processes can improve the readability and resolution of the results. Spectrogram and scalogram of the AE burst are obtained and compared to get the characteristics information. Renyi entropies are computed for various bilinear time-frequency transforms to evaluate the randomness. These bilinear transforms are reassigned by using the improved algorithm in discrete computation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.362-367
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• 1996

In this paper, the eigenstructure of a class of linear time varying systems, termed as linear quasi-time invariant(LQTI) systems, is investigated. A system composed of dynamic devices such as linear time varying capacitors and resistors can be an example of the class. To effectively describe and analyze the LQTI systems, a generalized differential operator G is introduced. Then the dynamic systems described by the operator G are studied in terms of eigenvalue, frequency characteristics, stability and an extended convolution. Some basic attributes of the operator G are compared with those of the differential operator D. Also the corresponding generalized Laplace transform pair is defined and relevant properties are derived for frequency domain analysis of the systems under consideration. As an application example, a LQTI circuit is examined by using the concept of eigenstructure of LQTI system. The LQTI filter processes the sinusoidal signals modulated by some functions.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.6
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• pp.551-561
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• 1991

The probabilistic generation simulation plays a key role in power system expansion and operational planning especially for the calculation of expected energy, loss of load probaility and unserved energy expected. However, it is crucial to develop a probabilistic generation simulation algorithm which gives sufficiently precise results within a reasonable computation time. In a previous paper, we have proposed an efficent method using Fast Hartley Transform in convolution process for considering the thermal and nuclear units. In this paper, a method considering the scheduling of pumped-storage plants and hydro plants with energy constraint is proposed. The method also adopts FHT techniques. We improve the model to include multi-state and multi-block generation. The method has been applied for a real size model system.

• Proceedings of the Korea Multimedia Society Conference
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• 2012.05a
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• pp.343-344
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• 2012

With the increase of sensitive data and their secure transmission and storage, the use of encryption techniques has become widespread. The performance of encoding majorly depends on the computational time, so a system with less computational time suits more appropriate as compared to its contrary part. Double Random Phase Encoding (DRPE) is an algorithm with many sub functions which consumes more time when executed serially; the computation time can be significantly reduced by implementing important functions in a parallel fashion on Graphics Processing Unit (GPU). Computing convolution using Fast Fourier transform in DRPE is the most important part of the algorithm and it is shown in the paper that by performing this portion in GPU reduced the execution time of the process by substantial amount and can be compared with MATALB for performance analysis. NVIDIA graphic card GeForce 310 is used with CUDA C as a programming language.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.145-147
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• 2006

Image resizing is to change an image size by upsampling or downsampling of a digital image. Most still images and video frames are given in a compressed domain on digital media. Image resizing of a compressed image can be performed in a spatial domain via decompression or recompression. In general, resizing of a compressed image in a compressed domain is much faster than that in a spatial domain. In this paper, we propose an approach to resize images in the integer discrete cosine transform (DCT) domain, which exploits the multiplication-convolution property of DCT.