• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.368-376
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• 2006

This paper describes a Fcore_GenSim(Parameterized FFT Core Generation & Simulation Program), which can be used as an essential If(Intellectual Property) in various OFDM modem designs. The Fcore_Gensim is composed of two parts, a parameterized core generator(PFFT_CoreGen) that generates Verilog-HDL models of FFT cores, and a fixed-point FFT simulator(FXP_FFTSim) which can be used to estimate the SQNR performance of the generated cores. The parameters that can be specified for core generation are FFT length in the range of 64 ~2048-point and word-lengths of input/output/internal/twiddle data in the range of 8-b "24-b with 2-b step. Total 43,659 FFT cores can be generated by Fcore_Gensim. In addition, CBFP(Convergent Block Floating Point) scaling can be optionally specified. To achieve an optimized hardware and SQNR performance of the generated core, a hybrid structure of R2SDF and R2SDC stages and a hybrid algorithm of radix-2, radix-2/4, radix-2/4/8 are adopted according to FFT length and CBFP scaling.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.5
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• pp.32-38
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• 2009

FTT(Fast Fourier Transform) processor is widely used in OFDM(Orthogonal Frequency Division Multiplesing) system. Because of the increased requirement of mobility and bandwidth in the OFDM system, they need large point FTT processor. Since the size of memory which stores the twiddle factor coefficients are proportional to the N of FFT size, we propose a new method by which we can reduce the size of the coefficient memory. In the proposed method, we exploit a counter and unsigned multiplier to generate the twiddle factor indices. To verify the proposed algorithm, we design TFCGs(Twiddle Factor Coefficient Generator) for 1024pint FFTs with R2SDF(Radix-2 Single-Path Delay Feedback), $R2^3SDF,\;R2^3SDF,\;R2^4SDF$ architectures. The size of ROM is reduced to 1/8N. In the case of $R2^4SDF$ architecture, the area and the power are reduced by 57.9%, 57.5% respectively.

• The Journal of the Acoustical Society of Korea
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• v.22 no.4
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• pp.269-275
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• 2003

In this paper, we proposed the robust watermark diminishing distortion of the original data inserting the watermark in specific coefficients of the frequency domain. In case the alpha is more than 0.5. we found that proposed watermark is detected by experiment of MP3, FFT, Cropping and Echo attack. Our proposed method improved the Cox's method in the SNR aspect.

• Proceedings of the KSEEG Conference
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• 1999.04a
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• pp.348-350
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• 1999

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.1
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• pp.35-41
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• 2020

Fast Fourier transform (FFT) processors have been widely used in various application such as communications, image, and biomedical signal processing. Especially, high-performance and low-power FFT processing is indispensable in OFDM-based communication systems. This paper presents a novel radix-26 FFT algorithm with low computational complexity and high hardware efficiency. Applying a 7-dimensional index mapping, the twiddle factor is decomposed and then radix-26 FFT algorithm is derived. The proposed algorithm has a simple twiddle factor sequence and a small number of complex multiplications, which can reduce the memory size for storing the twiddle factor. When the coefficient of twiddle factor is small, complex constant multipliers can be used efficiently instead of complex multipliers. Complex constant multipliers can be designed more efficiently using canonic signed digit (CSD) and common subexpression elimination (CSE) algorithm. An efficient complex constant multiplier design method for the twiddle factor multiplication used in the proposed radix-26 algorithm is proposed applying CSD and CSE algorithm. To evaluate performance of the previous and the proposed methods, 256-point single-path delay feedback (SDF) FFT is designed and synthesized into FPGA. The proposed algorithm uses about 10% less hardware than the previous algorithm.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.4
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• pp.23-27
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• 2010

This paper performs emotion classification test to find out the best parameter of electroencyphalogram(EEG) signal. Linear predictor coefficients, band cross-correlation coefficients of fast Fourier transform(FFT) and autoregressive model spectra are used as the parameters of 10-channel EEG signal. A multi-layer neural network is used as the pattern classifier. Four emotions for relaxation, joy, sadness, irritation are induced by four university students of an acting circle. Electrode positions are Fp1, Fp2, F3, F4, T3, T4, P3, P4, O1, O2. As a result, the Linear predictor coefficients showed the best performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.887-890
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• 2012

본 논문에서는 켑스트럼 계수의 변화에 따른 남성화자와 여성화자의 음향학적인 특징벡터를 비교하여 분석하는 기초적인 연구를 수행한다. 특히 FFT 켑스트럼 및 LPC 켑스트럼에 대한 남녀의 음향학적인 특징벡터의 차이점을 나타낸다. 향후 이러한 차이점을 기초로 하여 신경회로망 등에 의한 성별 인식에 대한 연구를 수행함으로써 남성화자 및 여성화자를 분리할 수 있는 근거를 마련하는 기초연구이다.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.5
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• pp.100-108
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• 2010

An autocorrelation method is used in pitch estimation. Autocorrelation values in time and frequency domains, which have different characteristics, correspond to the pitch period and fundamental frequency, respectively. We utilize an integrated autocorrelation method in time and frequency domains. It can remove the errors of pitch doubling and having. In the time and frequency domains, pitch period and fundamental frequency have reciprocal relation to each other. Especially, fundamental frequency estimation ends up as an error because of the resolution of FFT. To reduce these artifacts, interpolation methods are applied in the integrated autocorrelation domain, which decreases pitch errors. Moreover, only for the pitch candidates found in a time domain, the corresponding frequency-domain autocorrelation values are calculated with reduced computational complexity. Using linear interpolation, we can decrease the required number of FFT coefficients by 8 times. Thus, compared to the conventional methods, computational complexity can be reduced by 9.5 times.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2074-2084
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• 2001

la this paper, a new digital watermarking algorithm using wavelet transform in frequency domain is suggested. The wavelet coefficients of low frequency subband are utilized to embed the watermark, After the original image is transformed using discrete wavelet transform, their coefficients are transformed into efficient1y in Sequency domain. DCT and FFT transforms are utilized in this processing. Watermark image of general image format is transformed using DCT and the hiding watermark into wavelet coefficients is equally distributed in frequency domain. Next, these wavelet coefficients are performed with inverse transform. The detection process of watermark is performed with reverse direction to insertion process. In this paper, we developed core watermark technologies which are a data hiding technology to hide unique logo mark which symbolizes the copyright and a robust protection technology to protect logo data from external attack like as compression, filtering, resampling, cropping. The experimental results show that two suggested watermarking technologies are invisible and robust.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.237-242
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• 2011

This paper proposes a detection algorithm for each section which detects the voiced section, unvoiced section, and the silence section at each frame using a multi-layer perceptron neural network. First, a power spectrum and FFT (fast Fourier transform) coefficients obtained by FFT are used as the input to the neural network for each frame, then the neural network is trained using these power spectrum and FFT coefficients. In this experiment, the performance of the proposed algorithm for detection of the voiced section, unvoiced section, and silence section was evaluated based on the detection rates using various speeches, which are degraded by white noise and used as the input data of the neural network. In this experiment, the detection rates were 92% or more for such speech and white noise when training data and evaluation data were the different.