• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.70-76
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• 2013

In this paper, we propose the bandpass form of discrete prolate spheroidal sequences(DPSS) which have the maximal energy concentration in a given passband and as such are very appropriate to obtain a projection of signals. The basic properties of the bandpass DPSS are also presented. Assuming a signal satisfies the finite time support and the essential band-limitedness conditions with a known center frequency, signal representation and interpolation techniques for band-limited signals using the bandpass DPSS are introduced where the reconstructed signal has minimal out-of-band energy. Simulation results are given to present the usefulness of the bandpass DPSS for efficient representation of band-limited signal.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.680-683
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• 1987

The speech signal processing in the auditory system can be analysized based on two representations : Average discharge rate and Temporal discharge pattern. But the average discharge rate representation is restricted by the narrow dynamic range because of the rate saturation and the two tone suppression phenomena, and the temporal discharge pattern representation needs a sophisticate frequency analysis and synchrony measure. In this paper, a simple representation is proposed : using a model considering the interaction of Cochlear fluid-BM movement and a haircell model, the feature of speech signals (formant frequency and pitch of vowels) is easily estimated in the Average Synchronized Rate.

• Speech Sciences
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• v.12 no.2
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• pp.153-170
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• 2005

The sub-Nyquist nonuniform sampling (SNNS) and the perfect reconstruction (PR) formula are proposed for the development of a systematic method to obtain minimal representation of a speech signal. In the proposed method, the instantaneous sampling frequency (ISF) varies, depending on the least upper boundary of spectral support of a speech signal in time-frequency domain (TFD). The definition of the instantaneous bandwidth (IB), which determines the ISF and is used for generating the set of samples that represent continuous-time signals perfectly, is given. Also, the spectral characteristics of the sampled data generated by the sub-Nyquist nonuniform sampling method is analyzed. The proposed method doesn't generate the redundant samples due to the time-varying property of the instantaneous bandwidth of a speech signal.

• Journal of information and communication convergence engineering
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• v.7 no.3
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• pp.304-308
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• 2009

This paper proposes a new concept of a signal constellation of the recently introduced half-symbol-rate-carrier phase-shift keying (HSRC-PSK) modulations for bandwidth-efficient high speed data communications. Since the HSRC-PSK modulations contain different symbol energies representing the same bit sequences due to the loss of orthogonality of their HSRC signals, it is very hard to represent the symbol using the conventional signal constellation. To resolve the problem, two different energies are assigned to represent one symbol for the HSRC offset quadrature phase shift keying (OQPSK) modulation. Similarly, the different energies exist to display the different symbol for HSRC minimum shift keying (MSK) modulation. With the proposed signal space representation, HSRC-PSK symbol can easily be shown with a two-dimensional scatter plot which provides helpful information of evaluating HSRC-PSK signal's quality.

• Speech Sciences
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• v.12 no.4
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• pp.17-29
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• 2005

Time-frequency representation reveals some useful information about instantaneous frequency, instantaneous bandwidth and boundary of each AM-FM component of a speech signal. In many cases, the instantaneous frequency of each component is not constant. The variability of instantaneous frequency causes degradation of resolution in time-frequency representation. This paper presents a method of adaptively adjusting the transform kernel for preventing degradation of resolution due to time-varying instantaneous frequency. The transform kernel is the form of frequency modulated function. The modulation function in the transform kernel is determined by the estimate of instantaneous frequency which is approximated by first order polynomial at each time instance. Also, the window function is modulated by the estimated instantaneous. frequency for mitigation of fringing. effect. In the proposed method, not only the transform kernel but also the shape and the length of. the window function are adaptively adjusted by the instantaneous frequency of a speech signal.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06a
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• pp.674-679
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• 1994

Acoustic signal such as speech and scattered sound, are generally a nonstationary process whose frequency contents vary at any instant of time. For time-varying signal, whether a nonstationary or a deterministic transient signal, a traditional frequency domain representation does not reveal the contents of signal characteristics and may lead to erroneous results such as the loss of desired characteristics features or the mis-interpretation for a wrong conclusion. A time-frequency domain representation is needed to characterize such signatures. Pseudo Wigner-Ville distribution (PWVD) is ideally suited for portraying nonstationary signal time-frequency domain and carried out by adapting the fast Fourier transform algorithm. In this paper, the important properties of PWVD were investigated using both stationary and nonstationry signatures by numerical examples PWVD was applied to acoustic sigtnatures to demonstrate its application for time-ferquency domain analysis.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.43-51
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• 1995

In this paper, we propose a neural network with fuzzy preprocessor not only for improving the classifi¬cation accuracy but also for being able to classify objects whose attribute values do not have clear bound¬aries. The fuzzy input signal representation scheme is included as a preprocessing module. It transforms imprecise input in linguistic form and precisely stated numerical input into multidimensional numerical values. 'The transformed input is processed in the postprocessing module. The experimental results indi-cate the superiority of fuzzy input signal representation scheme in comparison to binary input signal rep¬resentation scheme and decimal input signal representation scheme.

• Korean Journal of Cognitive Science
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• v.19 no.1
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• pp.75-88
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• 2008

Visual scene contains lots of redundant information. To process this redundant information without increasing brain's volume, human visual system may summarize incoming information. If similar but different information are given to visual system, visual system extracts statistical properties of the information. One example of the statistical representation is representation of mean size. The mean representation is accurate and durable. The process of mean representation is suggested to be parallel. However, previous studies on the mean representation mostly used behavioral methods. The purpose of this study was to investigate which neural regions extracted the mean size of a set of circles using fMRI method. According to previous studies, BOLD signal of certain areas that were in charge of cousin stimuli decreased when the same stimuli presented repetitively. We used this paradigm and found that BOLD signal of right occipital area was decreased when same mean site was presented repeatedly. This results suggest that right occipital area is the locus of mean representation of visual stimuli.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.4
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• pp.433-441
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• 1992

This paper describes an algorithm that can efficiently analyze the ECG signal using frame knowledge representation technique. Input to the analysis process is a set of significant points which have been extracted from an original sampled signal(lead II) by the syntactic peak recognition algorithm. The hierarchical property of ECG signal is represented by hierarchical AND/OR graph. The semantic information and constraints of the ECG signal are desctibed by frame. As the control mechanism for labeling points, the search mechanism with the mixed paradigms of data-driven and model driven hypothesis formation, scoring function, hypothesis modification network and instance inheritance are used. We used the CSE database in order to evaluate the performance of the proposed algorithm.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.278-285
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• 2008

In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.