Footprint assembly was proposed to reduce the blurriness of texture mapped image by mipmapping. Even though it can improve the quality of texture mapped image, there are yet blurring due to the limitation of it's filter kernel. This paper proposes a novel texture filtering, called adaptive footprint assembly (AFA), to overcome the limitation of footprint assembly. The proposed method greatly improves the quality of texture mapped images.

This paper addresses the problem to extract moving object from the moving background in the mixed domain (MixeD), which makes it possible to carry the filtering in one dimension. Since the velocities of moving object and background are necessary for moving object extraction, we first estimate the velocities based on the appropriate spatial frequency point selection method in the MixeD. Then an optimal filter used for 1-D signal filtering is designed. By filtering 1-D signals over all spatial frequencies, signals with certain velocity vector are extracted, while the extracted image is obtained by applying the 2-D IDFT to the filtered signals. The simulation results show that the method can extract moving object based both on the correctly estimated velocity and the proposed optimal 1-D filter.

In this paper, we propose a frequency domain active noise control (ANC) system without a secondary path model. The proposed system is based on the frequency domain simultaneous perturbation (FDSP) method we have proposed. In this system, the coefficients of the adaptive filter are updated only by error signals. The conventional ANC system using the filtered-x algorithm becomes unstable due to the error between the secondary path, from secondary source to error sensor, and its model. In contrast, the proposed ANC system has the advantage not to use the model. In this paper, we show the principle of the proposed ANC system, and examine its efficiency through computer simulations.

This paper presents a novel approach to water pollution detection from remotely sensed low-platform mounted visible band camera images. We examine the feasibility of unsupervised segmentation for slick (oily spills on the water surface) region labelling. Adaptive and non adaptive filtering is combined with density modeling of the obtained textural features. A particular effort is concentrated on the textural feature extraction from raw intensity images using filter banks and adaptive feature extraction from the obtained output coefficients. Segmentation in the extracted feature space is achieved using Gaussian mixture models (GMM).

In this letter, blind adaptive H multiuser detection is developed by employing a generalized sidelobe canceler (GSC) with and without subweight partition scheme. It is shown that the adaptive H algorithm with subweight approach has the advantages of fast convergence speed, insensitivity of dynamic estimate error, and suitability for arbitrary ambient noise over the conventional H and the RLS-based adaptive algorithms.

Cost down of millimeter wave components, especially antenna duplexer, is a key for spreading millimeter wave communication systems. An excellent cost-performance antenna duplexer is proposed. It consists of two E-plane filters and a wave-guide circulator. The performance fluctuations due to manufacturing accuracies are studied by simulations and experiments. These results are very useful for cost-down of the practical duplexer without performance degradation.

We propose a three-dimensional structure on a planar substrate employing micromachining technology. A low-loss suspended structure incorporating a BCB membrane employing deep trench etching technology has been newly proposed. A micromachined suspended line structure using BCB membrane film enables us to realize a low loss planar resonator, which achieved an unloaded quality factor (Q-factor) of more than 280 at 60 GHz. We design low-loss filters and antennas built into silicon in a 60 GHz band. A low-loss filter realizes an insertion loss of 1.0 dB at 60 GHz and a patch antenna obtains a 3% bandwidth. In addition, we demonstrate a 60 GHz receiver front-end IC incorporating the planar filter and the antenna, and obtain good results. These techniques enable us to integrate various functions into a compact package even in millimeter-wave bands.

This paper proposes a multisegment dielectric resonator (MSDR) placed on a slotline for millimeter-wave filter applications. The MSDR structure, including a rectangular dielectric lump and a thin low-dielectric insert, is quite useful for adjusting the coupling between the slotline mode and the resonant mode, leading to improve the filter performances. In addition, by tuning dimensions of the MSDR, a sharp and clear notch response can be designed in the transmission parameter. We have demonstrated the filter characteristics both theoretically and experimentally, and showed the practical procedure for the design of MSDR filters.

The millimeter wave filter using two whispering-gallery mode dielectric disk resonators is presented in this paper. The coupling coefficients of dual disk resonators and the external Q values of the single resonator excited by a dielectric waveguide are investigated theoretically and experimentally. A 2-stage bandpass filter which is designed at the center frequency of 69.85 GHz with a bandwidth of 500 MHz shows a low-loss property of 1.8 dB insertion loss.

This paper introduces current-mode biquad using multiple current output operational transconductance amplifiers (OTAs) and grounded capacitors. The circuit configuration is obtained from a second-order integrator loop structure with loss-less and lossy integrators. The proposed circuit can realize low-pass, band-pass, high-pass, band-stop and all-pass transfer functions by suitably choosing the input and output terminals. And the circuit characteristics can be electronically tuned through adjusting the transconductance gains of OTAs. It is also made clear that the proposed circuit has very low sensitivities with respect to the circuit active and passive elements. An example is given together with simulated results by PSpice.

Although TE0nδ mode ceramic resonators are usually used at centimeter frequencies, they have difficulty in making wide-band band-pass filters in the millimeter-wave region due to the weak coupling factors between TE0nδ mode resonators and input/output waveguides. In order to overcome such difficulty, a band-widening technique of the ceramic resonator loaded band-pass filter has been proposed. The EHnmδ modes were regarded as spurious modes so far, but it is clear that the coupling factors are larger than those of the TE0nδ modes from the results of experimental considerations in this paper. By using the EH11δ mode ceramic resonators, 5-pole, 1 dB Chebyshev ripple NRD guide band-pass filter has been fabricated for the applications to broad-band millimeter-wave communication systems at 60 GHz. The filter has great advantages such as the wide pass-band beyond 2 GHz and low excess insertion loss of less than 0.3 dB.

In this paper we show that the neuron filter is effective for relaxing the coefficient sensitiveness of the Hopfield neural network for combinatorial optimization problems. Since the parameters in motion equation have a significant influence on the performance of the neural network, many studies have been carried out to support determining the value of the parameters. However, not a few researchers have determined the value of the parameters experimentally yet. We show that the use of the neuron filter is effective for the parameter tuning, particularly for determining their values experimentally through simulations.

A method to reduce the bandwidth between texture memory and the rasterization processor is proposed. It achieves the reduction by not fetching useless texels from texture memory in bilinear filtering. Since it does not depend on cache and loss compression, it can be used in applications where the reusability of texels is low and loss compression is prevented.

This paper proposes new recursive fixed-point smoother and filter using covariance information in linear continuous-time stochastic systems. To be able to treat the stochastic signal estimation problem, a performance criterion, extended from the criterion in the H filtering problem by introducing the stochastic expectation, is newly introduced in this paper. The criterion is transformed equivalently into a min-max principle in game theory, and an observation equation in the Krein spaces is obtained as a result. For γ2<, the estimation accuracies of the fixed-point smoother and the filter are superior to the recursive least-squares (RLS) Wiener estimators previously designed in the transient estimation state. Here, γ represents a parameter in the proposed criterion. This paper also presents the fixed-point smoother and the filter using the state-space parameters from the devised estimators using the covariance information.

Most of the image restoration filters proposed so far include parameters that control the restoration properties. For bringing out the optimal restoration performance, these parameters should be determined so as to minimize a certain error measure such as the mean squared error (MSE) between the restored image and original image. However, this is not generally possible since the unknown original image itself is required for evaluating MSE. In this paper, we derive an estimator of MSE called the subspace information criterion (SIC), and propose determining the parameter values so that SIC is minimized. For any linear filter, SIC gives an unbiased estimate of the expected MSE over the noise. Therefore, the proposed method is valid for any linear filter. Computer simulations with the moving-average filter demonstrate that SIC gives a very accurate estimate of MSE in various situations, and the proposed procedure actually gives the optimal parameter values that minimize MSE.

The adaptive system design by 16-bit fixed point processing enables to employ an inexpensive digital signal processor (DSP). The narrow dynamic range of such 16 bits, however, does not guarantee the same performance that is confirmed beforehand by computer simulations. A cause of degrading the performance originates in the operation halving the word length doubled by multiplication. This operation rounds off small signals staying in the lower half of the doubled word length to zero. This problem can be solved by limiting the multiplier to only its sign () like the signed regressor algorithm, named 'bi-quantized-x' algorithm in this paper, for the convenience mentioned below. This paper first derives the equation describing the convergence property provided by a type of signed regressor algorithms, the bi-quantized-x normalized least mean square (NLMS) algorithm, and then formulates its convergence condition and the step size maximizing the convergence rate. This paper second presents a technique to improve the convergence property. The bi-qiantized-x NLMS algorithm quantizes the reference signal to 1 according to the sign of the reference signal, whereas the technique moreover assigns zero to the reference signal whose amplitude is less than a predetermined level. This paper explains the principle that the 'tri-qunatized-x' NLMS algorithm employing the technique can improve the convergence property, and confirms the improvement effect by computer simulations.

This paper proposes distributed evolutionary digital filters (EDFs) as an improved version of the original EDF. The EDF is an adaptive digital filter which is controlled by adaptive algorithm based on evolutionary computation. In the proposed method, a large population of the original EDF is divided into smaller subpopulations. Each sub-EDF has one subpopulation and executes the small-sized main loop of the original EDF. In addition, the distributed algorithm periodically selects promising individuals from each subpopulation. Then, they migrate to different subpopulations. Numerical examples show that the distributed EDF has a higher convergence rate and smaller steady-state value of the square error than the LMS adaptive digital filter, the adaptive digital filter based on the simple genetic algorithm and the original EDF.

This paper proposes a design method of variable IIR digital filters based on balanced realizations and minimum round-off noise realizations of digital filters. Highly accurate variable digital filters are easily derived by the proposed method. The coefficient matrices of both realizations of second-order digital filters are obtained directly from prototype realizations. The filter coefficients of variable digital filters can be obtained by frequency transformations to the realizations. The filter coefficients are presented as truncated Taylor series for the purpose of reducing a number of calculations to tune the coefficients. However the proposed filters have highly accurate variable characteristics against the coefficient truncation since balanced realizations and minimum round-off noise realizations have very low coefficient sensitivities, which are invariant under the frequency transformations. Moreover, the dynamic ranges of the proposed filters are almost constant against the frequency transformations. Numerical examples show the effectiveness of the variable digital filters designed by the proposed method.

This paper presents a digital reaction-diffusion system (DRDS)--a model of a discrete-time discrete-space reaction-diffusion dynamical system--for designing new image processing algorithms inspired by biological pattern formation phenomena. The original idea is based on the Turing's model of pattern formation which is widely known in mathematical biology. We first show that the Turing's morphogenesis can be understood by analyzing the pattern forming property of the DRDS within the framework of multidimensional digital signal processing theory. This paper also describes the design of an adaptive DRDS for image processing tasks, such as enhancement and restoration of fingerprint images.

A unified polyphase representation of analysis and synthesis filter banks is introduced in this paper, and then the efficient implementation on digital signal processors (DSP) is investigated. Especially, the number of memory accesses, power consumption, processing accuracy and the required instruction cycles are discussed. Firstly, a unified representation is given, and then two types of procedures, SIMO system-based and MISO system-based procedures, are shown, where SIMO and MISO are abbreviations for single-input/multiple-output and multiple-input/single-output, respectively. These procedures are compared to each other. It is shown that the number of data load in SIMO system-based procedure is a half of that in MISO system-based procedure for two-channel filter banks. The implementation of M-channel filter banks is also discussed.