In this paper, a novel design method of critically sampled contourlet transform (CSCT) is proposed. The original CT which consists of Laplacian pyramid and directional filter bank provides efficient frequency plane partition for image representation. However its overcompleteness is not suitable for some applications such as image coding, its critical sampling version has been studied recently. Although several types of the CSCT have been proposed, they have problems on their realization or unnatural frequency plane partition which is different from the original CT. In contrast to the way in conventional design methods based on a "top-down" approach, the proposed method is based on a "bottom-up" one. That is, the proposed CSCT decomposes the frequency plane into small directional subbands, and then synthesizes them up to a target frequency plane partition, while the conventional ones decompose into it directly. By this way, the proposed CSCT can design an efficient frequency division which is the same as the original CT for image representation can be realized. In this paper, its effectiveness is verified by non-linear approximation simulation.

We propose a new band selective stop filter construction to decrease the out of band intermodulation distortion (IMD) noise generated in the transmitting power amplifier. Suppression of IMD noise directly improves the adjacent channel leakage power ratio (ACLR). A high-temperature superconducting (HTS) device with extremely high-Q performance with very small hybrid IC pattern would make it possible to implement the proposed filter construction as a practical device. To confirm the effectiveness of the HTS reaction-type filter (HTS-RTF) in improving ACLR, investigations based on both experiments and numerical analyses are carried out. The structure of a 5-GHz split open-ring resonator is investigated; its targets include high-unload Q-factor, low current densities, and low radiation. A designed 5-GHz HTS-RTF with 4 MHz suppression bandwidth and more than 40 dB MHz-1 sharp skirt is fabricated and experimentally investigated. The measured ACLR values are improved by a maximum of 12.8 dB and are constant up to the passband signal power of 40 dBm. In addition, to examine the power efficiency improvement offered by noise suppression of the HTS-RTF, numerical analyses based on measured results of gallium nitride HEMT power amplifier characteristics are conducted. The analyzed results shows the drain efficiency of the amplifier can be improved to 44.2% of the amplifier with the filter from the 15.7% of the without filter.

We report on the spurious suppression effect in low-microwave power transmitters by high temperature superconducting (HTS) bandpass filters (BPFs) which are promising for devices requiring BPFs with high-frequency selectivity. Some of the major issues on the power BPFs with HTS planar circuits for wireless communication applications are reviewed. As a case study for the HTS filter and its spurious suppression effect, this paper describes an example of the measured power spectrum density (PSD) on the suppression effect by one of our developed power BPFs with YBCO films for the 5 GHz band. It was designed with equivalent cascade resonators of 16 poles. We demonstrated the effect by HTS power filter in a power amplifier for the 5 GHz band.

A method for measuring similarity between two variables is presented. Our approach considers the case where available observations are arbitrarily filtered versions of the variables. In order to measure the similarity between the original variables from the observations, we propose an error-minimizing filter (EMF). The EMF is designed so that an error between outputs of the EMF is minimized. In this paper, the EMF is constructed by a finite impulse response (FIR) filter, and the error between the outputs is evaluated by the mean square error (EMF). We show that minimization of the MSE results in an eigenvalue problem, and the optimal solution is given in a closed form. We also reveal that the minimal MSE by the EMF is efficient in the measurement of the similarity from the viewpoint of a correlation coefficient between the originals.

We address the issue of MIMO channel estimation with the aid of a priori temporal correlation statistics of the channel as well as the spatial correlation. The temporal correlations are incorporated to the estimation scheme by assuming the Gauss-Markov channel model. Under the MMSE criteria, the Kalman filter performs an iterative optimal estimation. To take advantage of the enhanced estimation capability, we focus on the problem of channel estimation from a partial channel measurement in the MIMO antenna selection system. We discuss the optimal training sequence design, and also the optimal antenna subset selection for channel measurement based on the statistics. In a highly correlated channel, the estimation works even when the measurements from some antenna elements are omitted at each fading block.

This paper presents the regulation and dynamic characteristics of the dc-dc converter with digital PID control, the minimum phase FIR filter or the IIR filter, and then the design criterion to improve the dynamic characteristics is discussed. As a result, it is clarified that the DC-DC converter using the IIR filter method has superior performance characteristics. The regulation range is within 1.3%, the undershoot against the step change of the load is less than 2% and the transient time is less than 0.4 ms with the IIR filter method. In this case, the switching frequency is 100 kHz and the step change of the load R is from 50 Ω to 10 Ω . Further, the superior characteristics are obtained when the first gain, the second gain and the second cut-off frequency are relatively large, and the first cut-off frequency and the passing frequency are relatively low. Moreover, it is important that the gain strongly decreases at the second cut-off frequency because the upper band pass frequency range must be always less than half of the sampling frequency based on the sampling theory.

A novel error concealment method using a Kalman filter is presented in this paper. In order to successfully utilize the Kalman filter, its state transition and observation models that are suitable for the video error concealment are newly defined as follows. The state transition model represents the video decoding process by a motion-compensated prediction. Furthermore, the new observation model that represents an image blurring process is defined, and calculation of the Kalman gain becomes possible. The problem of the traditional methods is solved by using the Kalman filter in the proposed method, and accurate reconstruction of corrupted video frames is achieved. Consequently, an effective error concealment method using the Kalman filter is realized. Experimental results showed that the proposed method has better performance than that of traditional methods.

Two discrete-time Wirtinger-type inequalities relating the power of a finite-length signal to that of its circularly-convolved version are developed. The usual boundary conditions that accompany the existing Wirtinger-type inequalities are relaxed in the proposed inequalities and the equalizing sinusoidal signal is free to have an arbitrary phase angle. A measure of this sinusoidal signal's power, when corrupted with additive noise, is proposed. The application of the proposed measure, calculated as a ratio, in the evaluation of the power of a sinusoid of arbitrary phase with the angular frequency π/N, where N is the signal length, is thoroughly studied and analyzed under additive noise of arbitrary statistical characteristic. The ratio can be used to gauge the power of sinusoids of frequency π/N with a small amount of computation by referring to a ratio-versus-SNR curve and using it to make an estimation of the noise-corrupted sinusoid's SNR. The case of additive white noise is also analyzed. A sample permutation scheme followed by sign modulation is proposed for enlarging the class of target sinusoids to those with frequencies M π/N, where M and N are mutually prime positive integers. Tandem application of the proposed scheme and ratio offers a simple method to gauge the power of sinusoids buried in noise. The generalization of the inequalities to convolution kernels of higher orders as well as the simplification of the proposed inequalities have also been studied.

A static dependency pair method, proposed by us, can effectively prove termination of simply-typed term rewriting systems (STRSs). The theoretical basis is given by the notion of strong computability. This method analyzes a static recursive structure based on definition dependency. By solving suitable constraints generated by the analysis result, we can prove the termination. Since this method is not applicable to every system, we proposed a class, namely, plain function-passing, as a restriction. In this paper, we first propose the class of safe function-passing, which relaxes the restriction by plain function-passing. To solve constraints, we often use the notion of reduction pairs, which is designed from a reduction order by the argument filtering method. Next, we improve the argument filtering method for STRSs. Our argument filtering method does not destroy type structure unlike the existing method for STRSs. Hence, our method can effectively apply reduction orders which make use of type information. To reduce constraints, the notion of usable rules is proposed. Finally, we enhance the effectiveness of reducing constraints by incorporating argument filtering into usable rules for STRSs.

In this report, we propose a high-performance pipelined VLSI architecture of the LMS adaptive filter derived by a cut-set retiming technique. The proposed architecture has a peculiar pipelined form with 3 adaptation delays, and the FIR filter portion has a peculiar class of the transposed form providing a minimum output latency and coefficient delay. Both the delays, the adaptation delay and coefficient delay, are compensated by a look-ahead conversion. A new high-speed 4-input and 2-output CSA type adder with a small hardware is employed. The proposed architecture can achieve a good convergence property, high-sampling rate, minimum output latency, small hardware, and lower power dissipation, simultaneously, and is very suitable to implement on the VLSI.

In this paper, a Kalman filter-based method for restoration of video images acquired by an in-vehicle camera in foggy conditions is proposed. In order to realize Kalman filter-based restoration, the proposed method clips local blocks from the target frame by using a sliding window and regards the intensities in each block as elements of the state variable of the Kalman filter. Furthermore, the proposed method designs the following two models for restoration of foggy images. The first one is an observation model, which represents a fog deterioration model. The proposed method automatically determines all parameters of the fog deterioration model from only the foggy images to design the observation model. The second one is a non-linear state transition model, which represents the target frame in the original video image from its previous frame based on motion vectors. By utilizing the observation and state transition models, the correlation between successive frames can be effectively utilized for restoration, and accurate restoration of images obtained in foggy conditions can be achieved. Experimental results show that the proposed method has better performance than that of the traditional method based on the fog deterioration model.

Fast schemes for compressed-domain image size change, are proposed. Fast Winograd DCTs are applied to resizing images by a factor of two to one. First, we speed up the DCT domain downsampling scheme which uses the bilinear interpolation. Then, we speed up other image resizing schemes which use DCT lowpass truncated approximations. The schemes proposed here reduce the computational complexities significantly, while there is no difference in the overall quality of the images compared to previous works.

We propose a new filter method for feature selection for SELDI-TOF mass spectrum datasets. In the method, a new relevance index was defined to represent the goodness of a feature by considering the distribution of samples based on the counts. The relevance index can be used to obtain the feature sets for classification. Our method can be applied to mass spectrum datasets with extremely high dimensions and process the clinical datasets with practical sizes in acceptable calculation time since it is based on simple counting of samples. The new method was applied to the three public mass spectrum datasets and showed better or comparable results than conventional filter methods.

A double-capacitor phase error compensation configuration is proposed for Gm-C and MOSFET-C filters. The use of two capacitors enables the effective compensation capacitance to track with the tuning resistance, thereby making it more effective over a wider frequency tuning range as compared to the conventional single-capacitor configuration. Simulations of 5th-order Chebyshev filters in a 0.18 µm CMOS process with more than one octave tuning range were carried out to demonstrate the viability of the proposed double-capacitor configuration for both Gm-C and MOSFET-C filters.

We have proposed a noise reduction method based on a noise reconstruction system (NRS). The NRS uses a linear prediction error filter (LPEF) and a noise reconstruction filter (NRF) which estimates background noise by system identification. In case a fixed step size for updating tap coefficients of the NRF is used, it is difficult to reduce background noise while maintaining the high quality of enhanced speech. In order to solve the problem, a variable step size is proposed. It makes use of cross-correlation between an input signal and an enhanced speech signal. In a speech section, a variable step size becomes small so as not to estimate speech, on the other hand, large to track the background noise in a non-speech section.

This paper investigates noise reduction performance and performs convergence analysis of a Variable Error Data Normalized Step-Size Least Mean Square (VEDNSS LMS) algorithm. Adopting VEDNSS LMS provides fast convergence at early stages of adaptation while ensuring small final misadjustment. An analysis of convergence and steady-state performance for zero-mean Gaussian inputs is provided. Simulation results comparing the proposed algorithm to existing algorithms indicate its superior performance under various noise and frequency environments.

In this paper, we propose designing method for separable-denominator two-dimensional Infinite Impulse Response (IIR) filters (separable 2D IIR filters) by Successive Projection (SP) methods using the stability criteria based on the system matrix. It is generally known that separable 2D IIR filters are stable if and only if each of the denominators is stable. Therefore, the stability criteria of 1D IIR filters can be used for separable 2D IIR filters. The stability criteria based on the system matrix are a necessary and sufficient condition to guarantee stability in 1D IIR filters. Therefore, separable 2D IIR filters obtained by the proposed design method have a smaller error ripple than those obtained by the conventional design method using the stability criterion of Rouche's theorem.

We introduce the Rank M-type L (RM L)-filter to remove impulsive and speckle noise from corrupted images by means of use of DSP TMS320C6701.

A new formulation of equal-length asymmetric parallel coupled line (APCLs) having zero at z=-1 (θ = π) is employed to study band-stop filters. Such representations offer additional flexibility in the design of filter circuits through two extra variables. An optimization algorithm is used to tune the characteristic impedances of APCLs so that the transfer function of the signal line is close to the system function of an ideal prototype filter. Two band-stop filters are realized in the form of microstrip lines and their frequency responses are measured to validate this new formulation.

In this letter, a two channel frequency domain speech enhancement algorithm is proposed. The algorithm is designed to achieve better overall performance with relatively small array size. An improved version of adaptive null-forming is used, in which noise cancelation is implemented in auditory subbands. And an OM-LSA based postfiltering stage further purifies the output. The algorithm also features interaction between the array processing and the postfilter to make the filter adaptation more robust. This approach achieves considerable improvement on signal-to-noise ratio (SNR) and subjective quality of the desired speech. Experiments confirm the effectiveness of the proposed system.