In the present paper, a blind method is proposed to estimate QAM-OFDM channels of which transmitting and receiving stations are in line-of-sight, under the assumptions: i) the absolute value of phase rotation is less than π/2 at all sub-channels, and ii) for at least one sub-channel among them, it is less than π/4. From several simulation results for 50 sub-carriers with 16 QAM using 2048 OFDM blocks, it is confirmed that, when the SNR (Signal-to-Noise Ratio) in baseband region is over 20[dB], the QAM-OFDM channel is estimated at high precision by the proposed method and the restored symbols resulting from the channel estimates give the bit-error-rate about 10^-3 or less at SNR≥20[dB].

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In this paper, we proposed a dynamic time warping (DTW) method with a training part. DTW is a popular automatic speech recognition (ASR) method based on template matching. Conventional DTW is fast and of low complexity, however its recognition accuracy is limited. Recently, a DTW with multireferences (mDTW) algorithm has also been developed to improve the recognition accuracy to be comparable to that of the hidden Markov model (HMM) algorithm under noisy conditions. However the mDTW algorithm increases the calculation cost. Therefore, in order to reduce the calculation cost, in this paper, a training part will be added to the DTW-based ASR system, unlike the mDTW, which tries to find appropriate reference utterances to replace the increasing utterances. The results show that the average recognition accuracy of the proposed method is similar to that of the mDTW, and the calculation cost was reduced by 41.6%.

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In the field of mobile robot navigation, active beacons are a well researched tool to provide an infrastructure for guidance systems. One drawback to the use of active beacons is that their layout is sometimes arbitrary. Moreover, it is often determined solely by the researcher's preference or experience. While this is occasionally the easiest way to produce results, it is a significant roadblock to the general use of these systems in practical applications, as the layout for any installation must be evaluated by an expert user. In an attempt to formalize the placement of nodes in such a system, we have developed a straightforward approach for the placement of nodes. This approach has also been applied to a software tool which would allow even a novice user to generate layouts for their applications.

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In the research of robot vision, perspective display often needs to be generated from omnidirectional images. In this paper, we represent 360-degree immersive panorama by SCVT(Spherical Centroidal Voronoi Tessellation) image, referred to spherical bubble, and propose a method of quickly generating the perspective display from spherical bubble according to users' view direction and zoom-in/out operation. This process is done by employing the adjacent cues between neighboring cells and the pyramid data structure of spherical bubble. The experimental results are also presented to show the effectiveness of the proposed method.

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