This study examines treatment of a boundary between media to simulate an acoustic field using the CIP method. The handling of spatial derivatives of fields is extremely important for CIP acoustic field analysis. We demonstrate a method of handling this boundary and report results of CIP acoustic field analysis using the present treatment.

This paper describes a technique for controlling the degree of expressivity of a desired emotional expression and/or speaking style of synthesized speech in an HMM-based speech synthesis framework. With this technique, multiple emotional expressions and speaking styles of speech are modeled in a single model by using a multiple-regression hidden semi-Markov model (MRHSMM). A set of control parameters, called the style vector, is defined, and each speech synthesis unit is modeled by using the MRHSMM, in which mean parameters of the state output and duration distributions are expressed by multiple-regression of the style vector. In the synthesis stage, the mean parameters of the synthesis units are modified by transforming an arbitrarily given style vector that corresponds to a point in a low-dimensional space, called style space, each of whose coordinates represents a certain specific speaking style or emotion of speech. The results of subjective evaluation tests show that style and its intensity can be controlled by changing the style vector.

In the main part of this paper, we present a systematic discussion for the optimum interpolation approximation in a shift-invariant wavelet and/or scaling subspace. In this paper, we suppose that signals are expressed as linear combinations of a large number of base functions having unknown coefficients. Under this assumption, we consider a problem of approximating these linear combinations of higher degree by using a smaller number of sample values. Hence, error of approximation happens in most cases. The presented approximation minimizes various worst-case measures of approximation error at the same time among all the linear and the nonlinear approximations under the same conditions. The presented approximation is quite flexible in choosing the sampling interval. The presented approximation uses a finite number of sample values and satisfies two conditions for the optimum approximation presented in this paper. The optimum approximation presented in this paper uses sample values of signal directly. Hence, the presented result is independent from the so-called initial problem in wavelet theory.

Bicubic interpolation is one of the standard approaches for image magnification since it can be easily computed and does not require a priori knowledge nor a complicated model. In spite of such convenience, the images enlarged by bicubic interpolation are blurry, in particular for large magnification factors. This may be explained by four constraints of bicubic interpolation. Hence, by relaxing or replacing the constraints, we propose a new magnification method, which performs better than bicubic interpolation, but retains its compactness. One of the constraints is about criterion, which we replace by a criterion requiring that all pixel values are reproduced and preferential components in input images are perfectly reconstructed. We show that, by choosing the low frequency components or edge enhancement components in the DCT basis as the preferential components, the proposed method performs better than bicubic interpolation, with the same, or even less amount of computation.

In this paper, we propose a novel bicubic method for digital image interpolation. Since the conventional bicubic method does not consider image local features, the interpolated images obtained by the conventional bicubic method often have a blurring problem. In this paper, the proposed bicubic method adopts both the local asymmetry features and the local gradient features of an image in the interpolation processing. Experimental results show that the proposed method can obtain high accuracy interpolated images.

In this paper, we propose a new variable-bit-rate speech coder based on the waveform interpolation concept. After the coder extracts all parameters, the amounts of distortions between the current and the predicted parameters, which are estimated by extrapolation using the past two parameters, are measured for all parameters. A parameter is not transmitted unless the distortion exceeds the preset threshold. At the decoder side, the non-transmitted parameter is reconstructed by extrapolation with the past two parameters used to synthesize signals. In this way, we can reduce 26% of the total bit rate while maintaining the speech quality degradation below the 0.1 perceptual evaluation of speech quality (PESQ) score.

The objective of this paper is to develop the theoretical foundation to the pilot-assisted channel estimation using delay-time domain windowing for the coherent detection of OFDM signals. The pilot-assisted channel estimation using delay-time domain windowing is jointly used with polynomial interpolation, decision feedback and Wiener filter. A closed-form BER expression is derived. The impacts of the delay-time domain window width, multipath channel decay factor, the maximum Doppler frequency are discussed. The theoretical analysis is confirmed by computer simulation.

Detecting edge directions and estimating the exact value of a missing line are currently active research areas in deinterlacing processing. This paper proposes a spatial domain fuzzy rule that is based on an interpolation algorithm, which is suitable to the region with high motion or scene change. The algorithm utilizes fuzzy theory to find the most accurate edge direction with which to interpolate missing pixels. The proposed fuzzy direction oriented interpolator operates by identifying small pixel variations in seven orientations (0°, 45°, -45°, 63°, -63°, 72°, and -72°), while using rules to infer the edge direction. The Bayesian network model selects the most suitable deinterlacing method among three deinterlacing methods and it successively builds approximations of the deinterlaced sequence, by evaluating three methods in each condition. Detection and interpolation results are presented. Experimental results show that the proposed algorithm provides a significant improvement over other existing deinterlacing methods. The proposed algorithm is not only for speed, but also effective for reducing deinterlacing artifacts.

This paper proposes low-complexity blind detection for orthogonal frequency division multiplexing (OFDM) systems with the differential space-time block code (DSTBC) under time-varying frequency-selective Rayleigh fading. The detector employs the maximum likelihood sequence estimation (MLSE) in cooperation with the blind linear prediction (BLP), of which prediction coefficients are determined by the method of Lagrange multipliers. Interpolation of channel frequency responses is also applied to the detector in order to reduce the complexity. A complexity analysis and computer simulations demonstrate that the proposed detector can reduce the complexity to about a half, and that the complexity reduction causes only a loss of 1 dB in average Eb/N0 at BER of 10-3 when the prediction order and the degree of polynomial approximation are 2 and 1, respectively.

A direction-oriented spatial interpolation technique for image de-interlacing is presented in this letter. The experimental results demonstrate that our method achieves excellent performance in terms of both objective and subjective image quality. The proposed algorithm also has a very computationally simple structure, and proves to be a good candidate for low-cost hardware interpolator.

This paper proposes a compact interpolation scheme dedicated to a 1-dimensional position sensitive detector (PSD) with an optical sensing pixel array. The pixels are divided into even- and odd-numbered groups and winner take all (WTA) circuits are provided to each of the groups. The simulated results show that the detecting step-width is reduced to the half of the original one after applying the interpolation scheme.

In this paper, the interpolation line search (ILS) algorithm to find the desirable step length in a numerical optimization method is investigated to determine the optimal saturation limits with non-smooth nonlinearities. The simple steepest descent algorithm is used to illustrate that the ILS algorithm can provide adequate reductions in an objective function at minimal cost with fast convergence. The power system stabilizer (PSS) with output limits is used as an example for a nonlinear controller to be tuned. The efficient computation to implement the ILS algorithm in the steepest descent method is available by using the hybrid system model with the differential-algebraic-impulsive-switched (DAIS) structure. The simulation results are given to show the performance improved by the ILS algorithm.

This study presents an N-gram adaptation technique when additional text data for the adaptation do not exist. We use a language modeling approach to the information retrieval (IR) technique to collect the appropriate adaptation corpus from baseline text data. We propose to use a dynamic interpolation coefficient to merge the N-gram, where the interpolation coefficient is estimated from the word hypotheses obtained by segmenting the input speech. Experimental results show that the proposed adapted N-gram always has better performance than the background N-gram.

The perfect matched layer (PML) is formulated for the use in the constrained interpolation profile (CIP) method. Numerical results are presented to examine the performance of the proposed formulation of the PML in the case of two-dimensional TM wave. The results show that the proposed methods suppress the reflection effectively in comparison with the natural absorbing boundary condition of the CIP method. We have two methods to formulate the PML, and it is shown that the both methods have equal characteristics.

The application of Orthogonal Space-Time Block Codes (O-STBC) as the encoding scheme in the presence of "non-quasi-static" fading was considered. A simple and efficient adaptive method of channel estimation based on the interpolation of estimates acquired at the pre-amble and post-amble of framed blocks of information is developed. Moreover, the proposed method is proven, both theoretically and by simulations, to outperform the alternative of channel tracking, despite its significant low complexity.

Conventional video compression methods generally require a large amount of computation in the encoding process because they perform motion estimations. In order to reduce the encoding complexity for video compression, this paper proposes a new video compression method based on low-density parity check codes. The proposed method is suitable for resource-constrained devices such as mobile phones and satellite cameras.

This paper proposes a block-based video encoder employing variable frame skipping (VFS) to improve the video quality in low bit rate channel. The basic idea of VFS mechanism is to decide and skip a suitable, non-fixed number of frames in temporal domain to reduce bit usage. The saved bits can be allocated to enhance the spatial quality of video. In literature, several methods of frame skipping decision have been proposed, but most of them only consider the similarities between neighboring coded frames as the decision criteria. Our proposed method takes into account the reconstruction of the skipped frames using motion-compensated frame interpolation at decoder. The proposed VFS models the reconstructed objective quality of the skipped frame and, therefore, can provide a fast estimate to the frame skipping at encoder. The proposed VFS can determine the suitable frame skipping in real time and provide the encoded video with better spatial-temporal bit allocation.

This paper describes an approach to generating speech with emotional expressivity and speaking style variability. The approach is based on a speaking style and emotional expression modeling technique for HMM-based speech synthesis. We first model several representative styles, each of which is a speaking style and/or an emotional expression, in an HMM-based speech synthesis framework. Then, to generate synthetic speech with an intermediate style from representative ones, we synthesize speech from a model obtained by interpolating representative style models using a model interpolation technique. We assess the style interpolation technique with subjective evaluation tests using four representative styles, i.e., neutral, joyful, sad, and rough in read speech and synthesized speech from models obtained by interpolating models for all combinations of two styles. The results show that speech synthesized from the interpolated model has a style in between the two representative ones. Moreover, we can control the degree of expressivity for speaking styles or emotions in synthesized speech by changing the interpolation ratio in interpolation between neutral and other representative styles. We also show that we can achieve style morphing in speech synthesis, namely, changing style smoothly from one representative style to another by gradually changing the interpolation ratio.

This paper presents a color demosaicing method by introducing iterative asymmetric average interpolation. Missing primary colors on a Bayer pattern color filter array (CFA) are estimated by an asymmetric average interpolation where less intensity variation is assumed to be of stronger significance, before sharpness of an initial estimate is further improved by an iterative procedure. The iteration is implemented by an observation process followed by a restoration process. The former is modeled by blurring followed by CFA sampling and the latter is completely as same as the color demosaicing method initially applied. Experimental results have shown a favorable performance in terms of PSNR and visual appearance, in particular, in sharpness recovery.

In this paper, a pilot-assisted channel estimation using adaptive interpolation (in which, different interpolation filter tap weights is used for different symbol position) is proposed. Each set of tap weights is updated using the normalized least mean square (NLMS) algorithm, the reference signal for which is obtained by decision feedback and reverse modulation of the received data symbol. In order to reduce the number of tap weight sets and to achieve fast convergence, the conjugate centrosymmetry property of the tap weight set is used. The average bit error rate (BER) performance in a frequency-selective Rayleigh fading channel is evaluated by computer simulation. Also evaluated is the robustness against the frequency offset between a transmitter and a receiver.