• The KIPS Transactions:PartA
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• v.12A no.4 s.94
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• pp.305-312
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• 2005

In this paper, we present algorithm-level techniques for energy-efficient design at the algorithm level using FPGAs. We then use these techniques to create energy-efficient designs for two signal processing kernel applications: fast Fourier transform(FFT) and matrix multiplication. We evaluate the performance, in terms of both latency and energy efficiency, of FPGAs in performing these tasks. Using a Xilinx Virtex-II as the target FPGA, we compare the performance of our designs to those from the Xilinx library as well as to conventional algorithms run on the PowerPC core embedded in the Virtex-II Pro and the Texas Instruments TMS320C6415. Our evaluations are done both through estimation based on energy and latency equations on high-level and through low-level simulation. For FFT, our designs dissipated an average of $50\%$ less energy than the design from the Xilinx library and $56\%$ less than the DSP. Our designs showed an EAT factor of 10 times improvement over the embedded processor. These results provide a concrete evidence to substantiate the idea that FPGAs can outperform DSPs and embedded processors in signal processing. Further, they show that PFGAs can achieve this performance while still dissipating less energy than the other two types of devices.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.15 no.2
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• pp.122-127
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• 2004

Background and Objectives : Many studies have described and analyzed singer's formant and it has been shown that the epilaryngeal tube in the human airway is responsible for vocal ring, or the singer's formant. A similar phenomenon produced by trained singers in their speech led some authors to examine the speaker's ring. This study was designed to analyze the speaking voice of the singers and speaker's ring. Baterials and Methods : Ten tenors, fifteen baritones, fifteen sopranos and ten mezzo sopranos attending the music college, department of vocal music were chosen for this study. Fifteen male and fifteen female untrained normal speakers were chosen for control group. Each subject was asked to produce a sample of a sustained spoken vowel /ah/ sound for at least five seconds and read sentence 'Kaeul'. The sound data was analyzed using the Fast Fourier Transform(FFT) - based power spectrum, Long term average(LTA) power spectrum using the FFT algorithm of the Computerized Speech Lab(CSL, Kay elemetrics, Model 4300B, USA). Statistical analysis was performed using the Mann-Whitney test of the Statistical Package for Social Sciences(SPSS). Results : For LTA Power spectrum of/ah/ sound, a significant increase was seen in the 2,500-3,500Hz region(p<0.01) in four trained singer group compared with untrained speaker group, and a significant increase in the 9,000-10,000Hz region(p<0.01) in soparano group. Similarly, in sentence 'Kaeul', there was a significant increase in energy in the tenor, baritone, mezzo soprano group compared with the untrained speaker group in the 2,500-3,500Hz region(p<0.01), and a significant increase in all frequency region(p<0.01) in the soprano group. Conclusions : The LTA power spectrum suggests that trained singers group show more energy concentration in the 'singer's formant' region in the speaking voice, and authors believe this region to be the 'speaker's ring'. Further research is needed on the effect of singing training on the resonance of the speaking voice.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.9
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• pp.1028-1036
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• 2008

In the OFDM system, IQ imbalance problem happens at the RF front-end of transceiver, which degrades the BER(bit error rate) performance because it affects the constellation in the received signal. Also, phase noise is generated in the local oscillator of transceivers and it destroys the orthogonality between the subcarriers. Conventional PNS algorithm is effective for phase noise suppression, but it is not useful anymore when there are jointly IQ(In-phase and Quadrature) imbalance and phase noise. Therefore, in this paper, we analyze the effect of IQ imbalance and phase noise generated in the down-conversion of the receiver. Then, we estimate and compensate the IQ imbalance and phase noise at the same time. Compared with the conventional method that IQ imbalance after IFFT is estimated and compensated in front of FFT via the feedback, this proposed method extracts and compensates effect of IQ imbalance after FFT stage. In case IQ imbalance and phase noise exist at the same time, we can decrease complexity because it is needless to use elimination of IQ imbalance in time domain and training sequences and preambles. Also, this method shows that it reduces the ICI and CPE component using adaptive forgetting factor of MMSE after FFT.

• Journal of the Korean Society of Laryngology, Phoniatrics and Logopedics
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• v.15 no.1
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• pp.31-36
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• 2004

Background and Objectives : It has been shown that the epilaryngeal tube in the human airway is responsible for vocal ring, or the singer's formant. In previous study, authors showed that in trained tenors, besides the conventional singer's formant in the region of ,5500Hz, another energy peak was observed in the region of 8,000Hz. This peak was interpreted as the second resonance of the epilarynx tube. Singers in other voice categories who produce vocal ring are assumed to have the same peak, but no measurements have as yet been made. Materials and Methods : Fifteen tenors, fourteen baritones, seven sopranos and five mezzo sopranos attending the music college, department of vocal music who could reliably produce the head and chest registers were chosen for this study. Each subject was asked to produce an/ah/sound for at least three seconds for the head register sound(tenors ; G4, barions ; E4 sopranos ; F5 and mezzosopranos ; C5) and for the chest register sound (tenors ; C3, baritones ; D3, sopranos ; D4 and Mezzosoprano ; A3). The sound data was analyzed using the Fast Fourier Transform (FFT)-based power spectrum, Long term average(LTA) power spectrum using the FFT algorithm of the Computerized Speech Lab (CSL, Kay elemetrics, Model 4300B, USA). Statistical analysis was performed using the Mann-Whitney test of the Statistical Package for Social sciences(SPSS). Results : For head register sounds, a significant increase was seen in the 2,200-3,400Hz region(p<0.05) and the Similar to the head register sounds, there was a significant increase in energy in the four trained singer group compared with the untrained group in the 2,200-3,100Hz region(p<0.05), the 7,800-8,400Hz region(p<0.05) for the chest register sounds. Conclusions : When good vocal production was made for the head and chest registers, an energy peak was observed near 2,500Hz, a frequency already known as the "singer's formant', in all subjects in the study group. Another region of increased energy was observed around 8,000Hz that had not been noticed previously. The authors believe this region to be the second singer's formant.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.485-494
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• 2008

Huge amounts of various web items such as keywords, images, and web pages are being made widely available on the Web. The popularities of such web items continuously change over time, and mining temporal patterns in popularities of web items is an important problem that is useful for several web applications. For example, the temporal patterns in popularities of search keywords help web search enterprises predict future popular keywords, enabling them to make price decisions when marketing search keywords to advertisers. However, presence of millions of web items makes it difficult to scale up previous techniques for this problem. This paper proposes an efficient method for mining temporal patterns in popularities of web items. We treat the popularities of web items as time-series, and propose gapmeasure to quantify the similarity between the popularities of two web items. To reduce the computation overhead for this measure, an efficient method using the Fast Fourier Transform (FFT) is presented. We assume that the popularities of web items are not necessarily following any probabilistic distribution or periodic. For finding clusters of web items with similar popularity trends, we propose to use a density-based clustering algorithm based on the gap measure. Our experiments using the popularity trends of search keywords obtained from the Google Trends web site illustrate the scalability and usefulness of the proposed approach in real-world applications.