In this Paper, we propose an algorithm called partitioned recursive least square (PRLS) that involves a procedure that partitions a large data matrix into small matrices, applies RLS scheme in each of the small sub matrices and assembles the whole size estimation vector by concatenation of the sub-vectors from RLS output of sub matrices. Thus, the algorithm should be less complex than the conventional RLS and maintain an almost compatible estimation performance.

This paper has interest in the effect of a fine frequency offset, defined in ITU-T G.225, to the training performance of an adaptive equalizer. This paper uses Hilbert filter in configuring a transmission system model in order to let it get a frequency offset. Also additive white Gaussian noise and band-limited filter are considered. The signal received from the above transmission system applies to an adaptive equalizer with LMS algorithm, and its training procedures are investigated. As a result, we could find that even small fine frequency offset can severely deteriorate training performance of adaptive algorithm.

This paper presents a method for the automatic recognition of pitch accents with no prior knowledge about the phonetic content of the signal (no knowledge of word or phoneme boundaries or of phoneme labels). The recognition algorithm used in this paper is a time-delay recurrent neural network (TDRNN). A TDRNN is a neural network classier with two different representations of dynamic context: delayed input nodes allow the representation of an explicit trajectory F0(t), while recurrent nodes provide long-term context information that can be used to normalize the input F0 trajectory. Performance of the TDRNN is compared to the performance of a MLP (multi-layer perceptron) and an HMM (Hidden Markov Model) on the same task. The TDRNN shows the correct recognition of $91.9{\%}\;of\;pitch\;events\;and\;91.0{\%}$ of pitch non-events, for an average accuracy of $91.5{\%}$ over both pitch events and non-events. The MLP with contextual input exhibits $85.8{\%},\;85.5{\%},\;and\;85.6{\%}$ recognition accuracy respectively, while the HMM shows the correct recognition of $36.8{\%}\;of\;pitch\;events\;and\;87.3{\%}$ of pitch non-events, for an average accuracy of $62.2{\%}$ over both pitch events and non-events. These results suggest that the TDRNN architecture is useful for the automatic recognition of pitch accents.

A new type of high frequency wideband ultrasonic transducer with a separation between a transmitter and a receiver was proposed and its characteristics were simulated using a PSpice model. The piezoelectric ceramic $PbTiO_{3}$ as a transmitter and the piezoelectric copolymer P(VDF- TrFE) as a receiver were used for high sensitivity and wide bandwidth, respectively. The characteristics of the focusing transducer with center frequency of approximately 35MHz fabricated in this study showed very wide bandwidth, which could give an axial spatial resolution better than $30{\mu}m$ in B-mode image for biological tissues.

In this paper, we propose a critical banded wavelet packet-based spectral subtraction for speech enhancement. Critical banded wavelet packet, which reflects the human auditory system, may lead to minimization of intelligibility loss and quality improvement of the enhanced speech in the spectral domain, when combined with an appropriate spectral subtraction gain function. The proposed method shows better performance than the conventional one in comparative assessments. We also show that, for effective evaluation of enhanced speech, it is essential to consider the characteristics of speech quality measures.

It is generally known that accurate segmentation is very necessary for both an individual word and continuous utterances in speech recognition. It is also commonly known that techniques are now being developed to classify the voiced and the unvoiced, also classifying the plosives and the fricatives. The method for accurate recognition of the phonemes isn't yet scientifically established. Therefore, in this study we analyze the Korean language, using the classification of 'Hunminjeongeum' and contemporary phonetics, with the frequency band, Mel band and Mel Cepstrum, we extract notable features of the phonemes from Korean speech and segment speech by the unit of the phonemes to normalize them. Finally, through the analysis and verification, we intend to set up Phonemic Segmentation System that will make us able to adapt it to both an individual word and continuous utterances.

A laboratory study was carried out to investigate the change of ultrasonic velocity as a function of temperature for fluid mud (i.e., suspension). Pulse transmission technique with ultrasonic wave was used for ultrasonic velocity measurement. The five samples for fluid mud were prepared for concentration range of $30.6{\%}\;(1.24\;g/cm^{3}\;in\;density),\;23.3{\%}\;(1.19\;g/cm^{3}),\;11.5{\%}(1.10\;g/cm^{3}),\;7.8{\%}\;(1.08\;g/cm^{3}),\;and\;3.8{\%}\;(1.05\;g/cm^{3})$ by weight. The ultrasonic velocity in fluid mud was investigated to increase $(approximately\;2.83\;to\;4.95\;m/s/^{\circ}C)$ with increasing temperature, due to the effect of viscosity and compressibility of water with changing temperature. But the increasing rate tends to decrease at temperature higher than $30^{\circ}C,$ caused by the effect of viscosity. The concentration of fluid mud more affect to the ultrasonic velocity at higher temperature range than that at lower temperature. Overall the temperature effect on the ultrasonic velocity in fluid mud was a similar rate as for distilled water and seawater, suggesting fluid mud significantly depends on the behavior of water.