This paper describes an adaptive neural vector quantization algorithm with a deleting approach of weight (reference) vectors. We call the algorithm an adaptive learning and self-deleting algorithm. At the beginning, we introduce an improved topological neighborhood and an adaptive vector quantization algorithm with little depending on initial values of weight vectors. Then we present the adaptive learning and self-deleting algorithm. The algorithm is represented as the following descriptions: At first, many weight vectors are prepared, and the algorithm is processed with Kohonen's self-organizing feature map. Next, weight vectors are deleted sequentially to the fixed number of them, and the algorithm processed with competitive learning. At the end, we discuss algorithms with neighborhood relations compared with the proposed one. The proposed algorithm is also good in the case of a poor initialization of weight vectors. Experimental results are given to show the effectiveness of the proposed algorithm.

While high compression ratio has been achieved using recently developed image coding algorithm, the noise removal technique is considered as an important subject. This still holds for very low bitrate video coding, that is, MPEG-4 has defined it as a core experiment which is mainly concerned with block based discrete cosine transform (DCT) coding such as H.263 and MPEG-1. This paper describes a novel and practical technique which attempts to accomplish both noise suppression and detail preservation at the same time. Some of the conventional adaptive filters are designed to search a homogeneous region among the predetermined polygonal subregions, then to apply a smoothing operation within the selected subregion. It shall be, however noted that sometimes the predetermined subregion finally selected may still be hererogeneous. This fact leads us to a novel idea; instead of examining the predetermined regions, define a lot more flexible region likely to be homogeneous. In order to achieve this, we introduce the binary index. each pixel is classified into either the lower intensity group or higher intensity group based on a local statistics. Then a smoothing operation is applied within the pixels having the same group index as the pixel to be processed. Thus our scheme can search a homogeneous region appropriately. The adaptive smoothing adopted in the proposed scheme is also designed to be consistent with an important property of human visual system, i.e., the spatial masking. noise visibility decreases at spatial details such as edges and textures. Another advantage is that it can be realized with significantly low computations. The simulation results show that his approach can suppress the visible artifacts while retaining the fine details such as edge and texture.

M-ary orthogonal keying (MOK) systems under carrier frequency offset (CFO) are investigated. It is shown that spurious signals are introduced by the offset frequency components of spectrum after multiplication in correlation detection process, and some conditions on robust orthogonal signal sets are derived. Walsh function sets are found to be very weak against CFO, since they produce large spurious signals. As robust orthogonal signal sets against CFO, the rows of circulant Hadamard matrices are proposed and their error performanses are evaluated. The results show that they are good M-ary orthogonal signal sets in the presence of CFO.

The performance of an M-ary spread-spectrum multiple-access (M-ary/SSMA) scheme in the presence of carrier frequency offset is discussed in this paper. The influence of carrier frequency offset on the non-coherent reception of M-ary/SSMA signals is examined and it is shown that the carrier frequency offset degrades the performance remarkably, yet. this influence has a distinctive property. Making use of this property, we propose a new M-ary/SSMA scheme that can mitigate the influence of the carrier frequency offset. The scheme is based on the assignment of two distinctive Hadamard codes to in-phase and quadrature components of the transmitted signal. The effect of simultaneous transmission is evaluated in terms of bit-error-rate performance with the carrier frequency offset. As the result, it is observed that the satisfactory bit-error-rate performance can be achieved in the presence of carrier frequendy offset.

Hybrid direct sequence/slow frequency hopping-time division duplex (DS/SFH-TDD) multiple access system has some good features of each system. However it has a problem of hit between multiple users. If the designed frequency hopping patterns are inadequate, the quality of the multiple access system is degraded due to the frequent hit. In this paper, we propose an adaptive hopping pattern control system which is able to avoid the multiple access interference of hit. The proposed system decreases the influence of hit and increases the user capacity in the cell. And this adaptive hopping pattern control is applied to both single-cell and multi-cell systems. By computer simulation to evaluate the performance of this system, we found that this system is effective in increasing the multiple access capability.

This paper first presents the performance analysis of the NACF algorithm. The results show the possibility of the degradation in the convergence speed. To improve the convergence speed, the bias term is introduced into the NACF algorithm and its efficiency is investigated through the computer simulations.

High-resolution algorithms for the detection and estimation of Directions Of Arrival (DOA) such as MUSIC, lead to accurate results but require the computation of the noise-subspace through an expensive covariance matrix eigendecomposition. Adaptive estimators of the noise-subspace can be very useful in a non-stationary environment when the convergence is possible with a few number of snapshots. Some adaptive methods are presented showing that an indirect noise-subspace estimation through a signal subspace estimation can be advantageous both in terms of convergence rate and computation complexity during each update. Some computer simulations examples showing performances are provided.

The present paper investigates a two-dimensional (2-D) adaptive lattice filter used for modeling 2-D AR fields. The 2-D least mean square (LMS) lattice algorithm is used to update the filter coefficients. The proposed adaptive lattice filter can represent a wider class of 2-D AR fields than previous ones. Furthremore, its structure is also shown to possess orthogonality in the backward prediction error fields. These result in superior convergence and tracking properties to the adaptive transversal filter and other adaptive 2-D lattice models. Then, the convergence property of the proposed adaptive LMS lattice algorithm is discussed. The effectiveness of the proposed model is evaluated for parameter identification through computer simulation.

In many actual applications of the adaptive filtering, input signals as well as output signals often contain observation noises. Hence, it is necessary to develop an adaptive filtering algorithm to such an errors-in-variables (EIV) model. One solution for identifying the EIV model is a total least squares (TLS) algorithm based on a singular value decomposition of an off-line processing. However, it has not been considered to identify the EIV IIR system using an adaptive TLS algorithm of which stability has been guaranteed during adaptation process. Hence we propose a normalized lattice IIR adaptive filtering algorithm for the TLS parameter estimation. We also show the effectiveness of the proposed algorithm under noisy circumstances through simulations.

RCS fluctuation of targets such as ships can be reduced by the high-resolution radar. The high-resolution radar resolves the total radar echo into several parts which do not interfere each other. The reduction of interference gives stable target RCS. A simple model of the RCS fluctuation reduction is presented. Typical data for ships taken by an experimental radar which has range resolution about 0.75 m, are also shown. The analysis results show that the RCS fluctuation reduction agree with the simple model well.

In future mobile radio, high-speed transmission and efficient spectrum utilization will be important. However, multipath propagation with large delay difference and cochannel interference are obstacles to the advanced mobile communication system. An adaptive antenna can suppress multipath signals and cochannel interference signals. This paper reviews basic performance of multipath fading reduction and cochannel interference suppression using the adaptive antenna. After a brief explanation of adaptive antenna concepts, we show simulation and experimental results of the fading reduction. It is pointed out that the adaptive antenna cancels multipath signals with large delay difference strongly. This feature is very important for high-speed TDMA systems. Moreover, it is shown from simulation results that the adaptive antenna improves the spectrum efficiency by suppressing the cochannel interference signals.

Winter thundercloud on the coast of the Sea of Japan is difficult for the detection and forecast. This paper reports the new method of thundercloud detection using C-Band weather radar data and meteorological data from rawin sonde. This method includes the thunderclouds echo tracking and chronological evaluation of thundercloud life-cycle stages. The detection probability of critical area for cloud-to-ground lightning is over 90% on winter cloud echo data. This method is workable on realtime processing in work-station computer.

A new airborne rain radar named CAMPR (CRL Airborne Multiparameter precipitation Radar) has been developed for the major purpose of calibrating PR (Precipitation Radar) onboard TRMM (Tropical Rainfall Measuring Mission; scheduled to be launched in 1997) in orbit by observing the same rain with both CAMPR and TRMM satellite. CAMPR operates as a coherent radar at 13.8 GHz, the same frequency as TRMM-PR, and has polarimetric and Doppler capabilities. It is installed on a relatively small aircraft and can scan the antenna over a wide angle range, from the nadir to the near-horizon. These functions have been verified to work well and it is shown that the radar system is accurately calibrated. Examples of measurement data show CAMPR's high capability to extract various quantities relating to precipitation and cloud physics. Before the TRMM launch, CAMPR is being used to obtain TRMM-PR simulation data to help its algorithm development as well as to obtain data concerning precipitation and cloud physics.

We have compared the various raindrop-size distributions (DSD) with the recent experimental data collected by the distrometer. It is shown that the Weibull distribution is the best fit to the experimental data for drizzle, widespread and thunderstorm rain cases. By using this Weibull DSD, we obtained a new expression of the radar reflectivity factor (Z) and the rainfall rate (R) relation, that is Z=285R1.48, which gives few errors comparing to some measurements in TRMM frequency of 14GHZ.

A method to correct the path-integrated attenuation derived from spaceborne radar measurement for the non-uniform beam filling (NUBF) effect is studied . A preliminary test using the data obtained from shipborne and ground-based radars is performed. It is found that the relation between the coarse-scale variability (radar-measurable quantity, σL) and the fine-scale variability (a quantity necessary for the NUBF correction, σH) of rain depends somewhat upon the rain cases studied and there still remains some underestimation in the corrected results. Nevertheless, the test result demonstrates the potential of utilizing the "local" statistical properties of rain in order to decrease the bias error in rain rate estimation caused by the NUBF.

A verification is made on the accuracy of Radar-AMeDAS precipitation, which represents hourly precipitation over the Japanese Islands and the surrounding sea area with a spatial resolution of 5km using data from 5cm conventional radars, 10cm Fujisan Radar, and Automated Meteorological Data Acquisition System (AMeDAS) raingauge network. By comparing with data from a very dense raingauge network of the Tokyo Metropolitan Government, it is found that 1) Radar-AMeDAS precipitation shows good agreement if a positioning error of one pixel of 5km square is allowed 2) Radar-AMeDAS precipitation represents almost the average of raingauge measurements in the 5km square for most of the precipitation caused by a large scale disturbance, and 3) Radar-AMeDAS precipitation is close to the maximum raingauge measurement in the pixel when precipitation is extremely localized such as thunderstorms or showers. Radar-AMeDAS precipitations are compared also with AMeDAS measurements statistically with respect to the appearance rates, that is (total number of pixels where specific intensity is observed) / (total number of all pixels), for different precipitation intensities. The rate of Radar- AMeDAS precipitation shows excellent agreement with that of AMeDAS if radar echoes are observed at the altitude lower than 2km. Since Radar- AMeDAS precipitation on land sometimes represents the maximum of precipitation in a pixel for the purpose of unfailingly detecting extremely localized severe precipitation, it shows a high appearance rate at high precipitation intensity than AMeDAS, which is considered to represent statistically the average of a pixel. As a result, in estimating areal rainfall amounts, Radar- AMeDAS precipitation overestimates AMeDAS measurement by 8% at 5mm/h and by 12% at 40mm/h. Radar- AMeDAS precipitation over the sea, with no local calibration by AMeDAS and with little influence of orography, is 2% weaker in intensity than AMeDAS at 10mm/h, and 12% at 40mm/h.

Several major aircraft accidents have been attributed to low-altitude wind shears, which are normally caused by microbursts or gust fronts. Terminal Doppler Weather Radar (TDWR) systems are being installed near major airports for the detection of low-altitude wind shears. In order to develop a TDWR system further, low-altitude wind shears were numerically simulated in this study. The basic equations, which contain prognostic equations for air velocity, pressure, temperature, water vapor, and rainwater, were solved using a finite difference scheme. A terrain-following coordinate transformation was employed to simulate terrain effects. The simulation results are presented in this paper.

A maximum diameter (Dmax) of raindrop should be assumed when rainfall rate (R) is estimates from the differential reflectivity (ZDR) and the horizontal reflectivity (ZH) measured with dual-polarization radar. If the assumed Dmax is different from actual Dmax, the estimated R contains errors. Using distrometer data, it was found that ZDR correlates with Dmax, and it was verified that when Dmax is adaptively determined by an empirical relationship between ZDR and Dmax, errors in estimated R can be reduced.

A region-based adaptive perceptual quantization technique is proposed for video sequence coding, and applied to the MPEG coder. The visibility of coding artifacts in a macroblock (MB) is affected by perceptual characteristics of neighboring MBs as well as the MB itself. Therefore spacial and temporal activities of the MB and its surroundings are used to decide the quantization scaling factor. In comparison with the adaptive scheme in the encoding algorithm specified in MPEG-2 Test Model 5 (TM5), the proposed scheme is proven to improve perceptual quality further in video coding.

Weather clutter was measured using an L-band long-range (200 nmi.) air-route surveillance radar (ARSR), from the stored data of five scans. It is shown that weather clutter obeys a Weibull distribution, and moreover such Weibull-distributed weather clutter also obeys a Weibull distribution after passing through a moving target indicator (MTI) processor realized by a double canceller. Some adaptive methods for suppressing Weibull-distributed clutter are summarized.