In many applications involving the processing of noisy signals, it is desired to know the noise variance. This paper proposes a new method for estimating the noise variance from the signals of autoregressive (AR) and autoregressive moving-average (ARMA) systems corrupted by additive white noise. The method proposed here uses the low-order Yule-Walker (LOYW) equations and the lattice filter (LF) algorithm for the estimation of noise variance from the noisy output measurements of AR and ARMA systems, respectively. Two techniques are proposed here: iterative technique and recursive one. The accuracy of the methods depends on SNR levels, more specifically on the inherent accuracy of the Yule-Walker and lattice filter methods for signal plus noise system. The estimated noise variance is used for the blind indentification of AR and ARMA systems. Finally, to demonstrate the effectiveness of the method proposed here many numerical results are presented.

This paper presents an adaptive MLSE (Maximum Likelihood Sequence Estimator) suitable for TDMA cellular systems. The proposed MLSE has two special features such as handling wide dynamic range signals without analogue gain controls and fast channel tracking capability. In order to handle wide dynamic range signals without conventional AGCs (Automatic Gain Controller), the proposed MLSE uses envelope components of received signals obtained from a non-linear log-amplifier module which has wide log-linear gain characteristics. By using digital signal processing technique, the log-converted envelope components are normalized and converted to linear values which conventional adaptive MLSEs can handle. As a channel tracking algorithm of the channel estimator, the proposed MLSE adopts a QT-LMS (Quick-Tracking Least Mean Square) algorithm, which is obtained by modifying LMS algorithm to enable a faster tracking capability. The algorithm has a fast tracking capability with low complexity and is suitable for implementation in a fixed-point digital signal processor. The performances of the MLSE have been evaluated through experiments in TDMA cellular environments with π/4-shifted QPSK, 24.3k symbol/sec. It is shown that, under conditions of 65dB amplitude variations and 80Hz Doppler frequency, the MLSE successfully achieves less than 3% B.E.R., which is required for digital cellular systems.

Antenna selection diversity is an effective method to achieve both better transmission performance and compact circuit implementation in TDMA portable radio communications. However, diversity performance in fast fading environments is insufficient. This paper proposes a novel predictive antenna selection diversity scheme, PASD, which improves the diversity performance for higher fading rates. In PASD, received signal power for the assigned data slot is predicted from previously measured data. Thus, selection errors due to the receiving power changes caused by fast Rayleigh fading can be effectively avoided. An experimental result for a 3-ch TDMA system with a frame duration of 20ms shows that the diversity gain was increased by 1.3dB over the conventional method for a fading rate of 40Hz. PASD is also shown to have improved diversity performance against cochannel interference.

The paper proposes a new multicarrier 16QAM system for high-quality and high-bit-rate transmission with high spectral efficiency in land mobile radio communications. The proposed system uses a multicarrier transmission scheme to provide immunity against frequency-selective fading distortion. It also uses pilot-symbol-aided 16QAM to increase spectral efficiency, and it combines space diversity and FEC with maximum likelihood decoding to improve the bit error rate (BER) performance. Computer simulation shows that a BER of less than 10-4 is obtained over frequency-selective fading channels with rms delay spread of less than 5.4µs. Using a bandwidth of 200kHz the proposed system can achieve high-quality transmission with a total information rate of 256kbit/s.

The joint estimation of two unknowns, i.e. system and input sequence, is overviewed in two methodologies of equalization and identification. Statistical approaches such as optimizing the ensamble average of the cost function at the equalizer output have been widely researched. One is based on the principle of distribution matching that total system must be transparent when the equalizer output has the same distribution as the transmitted sequence. Several generalizations for the cost function to measure mis-matching between distributions have been proposed. The other approach applies the higher order statistics like polyspectrum or cumulant, which possesses the entire information of the system. For example, the total response can be evaluated by the polyspectrum measured at equalizer output, and by zero-forcing both side of the response tail the time dependency in the equalizer output can be eliminated. This is based on the second principle that IID simultaneously at input and at output requires a tranparent system. The recent progress of digital mobile communication gives an incentive to a new approach in the Viterbi algorithm. The Viterbi algorithm coupled with the blind channel identification can be established under a finite alphabet of the transmitted symbols. In the blind algorithm, length of the candidate sequence, which decides the number of trellis states, should be defined as long enough to estimate the current channel response. The channel impairments in mobile communication, null spectrum and rapid time-variance, are solved by fast estimation techniques, for example by Kalman filters or by direct solving the short time least squared error equations. The question of what algorithm has the fastest tracking ability is discussed from algebraic view points.

A receiving system suitable for multipath fading channels with co-channel interference is described. This system is equipped with both an M-sectored directional antenna and an adaptive equalizer to mitigate the influence due to multipath propagation and co-channel interference. By using directional antennas, this receiving system can separate desirable signals from undesirable signals, such as multipath signals with longer delay time and co-channel interference. It accepts multipath signals which can be equalized by maximum likelihood sequence estimation, and rejects both multipath signals with longer delay time and co-channel interference. Based on computer simulation results, the performance of the proposed receiving system is analyzed assuming simple propagation models with Rayleigh-distributed multipath signals and co-channel interference.

This paper proposes a new strategy for reducing contention for a critical section in a multiprocessor system and shows that the strategy can improve CPU utilization by several percent. Using simulation and queueing theory, it also discusses when the strategy is superior to conventional ones.

When measuring the ejection fraction for the evaluation of the ventricular pumping function by means of the thermodilution technique, the slow response a conventional thermistor has caused it to be considered unsuitable, and fast thermistors have been proposed as an alternative. However, in this paper we propose improving the time-domain response of a conventional thermistor using a signal processing technique composed of a series of first-order high-pass filters which is known as the natural observation system. We considered the rise time of the thermistor in response to a step temperature change to effect correction for the measurement of the ejection fraction. The coefficients of the natural observation system were calculated by minimizing the square error between the step-response signal of the thermistor and the band-limited reference signal. In an experiment using a model ventricle, the thermodilution curve obtained from a conventional thermistor was improved using the proposed technique, thus enabling successful measurement of the ejection fraction of the ventricles.

This paper proposes a new adaptive Interference Cancelling Equalizer (ICE) with a blind algorithm. From a received signal, ICE not only eliminates inter-symbol interference, but also cancels co-channel interference. Blind ICE can operate well even if training signals for the interference are unknown. First, training signal conditions for applying blind ICE are considered. Next, a theoretical derivation for blind ICE is developed in detail by applying the maximum likelihood estimation theory. It is shown that RLS-MLSE with diversity, which is derived for mobile radio equalizers, is also effective for blind ICE. Computer simulations demonstrate the 40kb/s QDPSK transmission performance of Blind ICE as a blind canceller with two branch diversity reception under Rayleigh fading in a single interference environment. The simulations assume synchronous training; the canceller is trained for the desired signal but not for the interference signals. Blind ICE can be successfully achieved at more than -10dB CIR values when average Eb/N0 is 15dB and a maximum Doppler frequency is 40Hz.

Myoelectric (ME) signals during dynamic movement suffer from motion arifact noise caused by mechanical friction between electrodes and the skin. It is difficult to reject artifact noises using linear filters, because the frequency components of the artifact noise include those of ME signals. This paper describes a nonlinear method of eliminating artifacts. It consists of an inverse autoregressive (AR) filter, a nonlinear filter, and an AR filter. To deal with ME signals during dynamic movement, we introduce an adaptive procedure and fuzzy rules that improve the performance of the nonlinear filter for local features. The result is the best ever reported elimination performance. This fuzzy rule based adaptive nonlinear artifact elimination filter will be useful in measurement of ME signals during dynamic movement.

In this paper, the relationship between the recursive least square (RLS) method with a U-D decomposition algorithm and ARMA lattice filter realization algorithm is presented. Both the RLS method and the lattice filter realization algorithm are used for the same applications, such as model identification, etc., therefore, it is expected that the lattice filter algorithm is in some ways related to the RLS. Though some of the proposed lattice filter algorithms have been derived by the RLS method, they do not express the relationship between RLS snd ARMA lattice filter realization algorithm. In order to describe the relation clearly, a new structure of ARMA lattice filter is proposed. Further, based on the relationship, a method of model identification with frequency weighting (MIFW), which is different from a previous method, is derived. The new MIFW method modifies the lattice parameters which are acquired without a frequency weighting and obtain the parameters of an ARMA model, which is identified with frequency weighting. The proposed MIFW method has the following restrictions: (1) The used frequency weighting is FIR filter with a low order. (2) By using the parameters of the ARMA lattice filter with ARMA (N,M) order and the frequency weighting with L order, the new ARMA parameter with the frequency weignting is with ARMA(N-L,M-L) order. By using the proposed MIFW method, the ARMA parameters estimated with the frequency weighting can be obtained without starting the computation again.

Efficiency of Cerenkov-radiation-type second harmonic generation with absorption loss for second harmonic wave is analytically estimated. Output power reduction for attenuation coefficient of 2.0104 cm1 is calculated 37% (63% output of lossless case). Blue SHG at 443.5 nm is observed by a poled polymer pNAn-PVA waveguide. The wavelength is shorter than the cut-off wavelength of 480 nm.

An adaptive array antenna can be considered as a useful tool of combating with fading in mobile communications. We can directly obtain the optimal weight coefficients without updating in temporal sampling, if the arrival angles and signal-to-noise ratio (SNR) of the desired and the undesired signals can be accurately estimated. The Maximum Entropy Method (MEM) can estimate the arrival angles, and the SNR from spatially sampled signals by an array antenna more precisely than the Discrete Fourier Transform (DFT). Therefore, this paper proposes and investigates an adaptive array antenna based on spatial spectral estimation using MEM. We call it MEM array. In order to reduce complexity for implementation, we also propose a modified algorithm using temporal updating as well. Furthermore, we propose a method of both improving estimation accuracy and reducing the number of antenna elements. In the method, the arrival angles can be approximately estimated by using temporal sampling instead of spatial sampling. Computer simulations evaluate MEM array in comparison with DFT array and LMS array, and show improvement owing to its modified algorithm and performance of the improved method.

We develop a convergence theory of the simple genetic algorithm (SGA) for two-bit problems (Type I TBP and Type II TBP). SGA consists of two operations, reproduction and crossover. These are imitations of selection and recombination in biological systems. TBP is the simplest optimization problem that is devised with an intention to deceive SGA into deviating from the maximum point. It has been believed that, empirically, SGA can deviate from the maximum point for Type II while it always converges to the maximum point for Type I. Our convergence theory is a first mathematical achievement to ensure that the belief is true. Specifically, we demonstrate the following. (a) SGA always converges to the maximum point for Type I, starting from any initial point. (b) SGA converges either to the maximum or second maximum point for Type II, depending upon its initial points. Regarding Type II, we furthermore elucidate a typical sufficient initial condition under which SGA converges either to the maximum or second maximum point. Consequently, our convergence theory establishes a solid foundation for more general GA convergence theory that is in its initial stage of research. Moreover, it can bring powerful analytical techniques back to the research of original biological systems.

This paper reviews recent progress in adaptive signal processing techniques for digital mobile radio communications. In Radio Signal Processing (RSP) , digital signal processing is becoming more important because it makes it relatively easy to develop sophisticated adaptive processing techniques, Adaptive signal processing is especially important for carrier signal processing in RSP. Its main objective is to realize optimal or near-optimal radio signal transmission. Application environments of adaptive signal processing in mobile radio are clarified. Adaptive equalization is discussed in detail with the focus on adaptive MLSE based on the blind algorithm. Demodulation performance examples obtained by simulations and experiments are introduced, which demonstrates the recent advances in this field. Next, new trends in adaptive array processing, interference cancelling, and orthogonalization processing are reviewed. Finally, the three automatic calibration techniques that are based on adaptive signal processing are described for realizing high precision transmission devices.

An adaptive method analyzing analytic speech signals is proposed in this paper. The method decreases the errors of finite precision on calculation in a method with real coefficients. It is shown from the results of experiments that the proposed method is more useful than adaptive methods with real coefficients.

We discuss estimation error as a basic problem in formant estimation in the analysis of speech of very short-time duration in the glottal closure of the vowel. We also show in our simulation that good estimation of the first formant is almost impossible with the ordinary method using a waveform cutting. We propose a new method in which the cut waveform, as a discontinuous function of finite time, is mapped to a continuous function defined in the whole time domain; and we show that using this method, the estimation accuracy for low frequency formants can be greatly improved.

This paper describes blue second harmonic generation (SHG) by an organic crystal of 2-furyl methacrylic anhydride (FMA). It has short cut-off wavelength of 380 nm and SHG coefficients at 1064 nm. d3324 pm/V and d3116 pm/V. In 900 nm region 90-degree phase-matched blue SHG is observed using a Ti: Sapphire laser as a fundamental source. This crystal is not hygroscopic and does not exhibit sublimation at room temperature. Fine polishing is also possible.

The performance of selection diversity combined with decision feedback equalizer for reception of TDMA carriers is investigated in this paper. The second generation digital land mobile communication systems standardized in the U.S., Japan, and Europe employ TDMA carriers at transmission bit rates up to several hundreds kbit/s. In order to provide higher quality of mobile communications services to the user with employing TDMA carriers, the systems would require both diversity and equalization techniques to combat attenuation of received signal power level due to Rayleigh fading and intersymbol interference resulting from time-variant multipath fading, respectively. This paper proposes a novel integration method of selection diversity and decision feedback equalization techniques which provides the better bit error rate performance than that for the conventional selection diversity method with decision feedback equalizer. The feature of proposed method is that selection diversity and decision feedback equalization techniques are integrated so as to interwork each other. We call the proposed method by the Decision Feedback Diversity with Decision Feedback Equalizer. The detailed algorithm of the proposed method is first presented, and then the system parameters for the method are evaluated based on the computer simulation results. Finally the computer simulation results for the performance of the proposed method are presented and compared to those for the conventional Selection Diversity with Decision Feedback Equalizer and the conventional Dual Diversity Combining and Equalization method under the typical mobile radio environments, in order to demonstrate the validity of the proposed method.

This paper discusses the asynchronous and synchronous parallel derivation of languages based on standard formal grammars. Some of the synchronous languages defined in this paper are essentially equivalent to the languages of E0L and EIL systems. Languages with restrictions on the number of parallel derivation steps are difined so that a t-time language is the set of strings w derived in t(w) or less parallel derivatio steps, where t(n) is an integer function. the properties of asynchronous derivation are generally discussed to clarify their conditions so that the derivation results are independent of the order in which productions are applied. It is shown that: (1) Any context sensitive grammar (CSG) G can be transformed into a CSG G such that the language generated by synchronous derivation in G is equal to that generated by asynchronous derivation in G , and vice versa; (2) Any regular language is a log-time context free language (CFL); (3) The class of CFLs is incomparable with that of log-time CSLs; and (4) If there is a bounded cellular automaton recognizing any language L in time T(n), then L is an O(T(n))-time CSL.