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.

This paper presents a structure of adaptive equalizer equipped with a neural network and a Viterbi decoder, and evaluates its performance under a fading environment by means of computer simulation.

A parallel quicksort algorithm in Ada is proposed and analyzed, its computational complexities are derived, and its performance profile is determined by simulation.

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.

The generation and design of a stationary Markov signal are discussed as an inverse problem, in which one looks for a transition probability when a stationary probability distribution is given. This paper presents a new solution to the inverse problem, which makes it possible to design and generate a Markov random signal with arbitrary probability distribution and an exponential correlation function. Several computer results are illustrated in figures.

The linear array processor architecture is an important class of interconnection structures that are suitable for VLSI. In this paper we study the problem of mapping a task tree onto a linear array to minimize the total execution time. First, an optimization algorithm is presented for a message scheduling probrem which occurs in the task tree mapping problem. Next, we give a heuristic algorithm for the task tree mapping problem. The algorithm partitions the node set of a task tree into clusters and maps these clusters onto processors. Simulation experiments showed that the proposed algorithm is much more efficient than a conventional algorithm.

The data-driven model of computation is well suited for flexible and highly parallel simulation of neural networks. First, the operational semantics of data-driven languages preserve the locality and functionality of neural networks, and naturally describe their inherent parallelism. Second, the asynchronous data-driven execution facilitates the implementation of large and scalable multiprocessor systems, which are necessary to obtain considerable degrees of simulation sppedups. In this paper, we present a dynamic data-driven multiprocessor system, and demonstrate its suitability for the paralel simulation of back propagation neural networks. Two parallel implementations are described and evaluated using an image data compression network. The system is scalable, and as a result, the performance improved proportionally with the increase in number of processors.

It is an important problem whether or not we can reject the disturbances from distributed parameter circuit. In order to analyze this problem structurally, it is necessary to investigate the basic equation of distributed parameter circuit in the framework of state space. Since the basic equation has two parameters for time and space, the state value belongs to an infinite-dimensional space. In this paper, the disturbance-rejection problems with incomplete state feedback and/or incomplete state feedback and feedforward for infinite-dimensional systems are studied in the framework of geometric approach. And under certain assumptions, necessary and/or sufficient conditions for these problems to be solvable are proved.

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.

The possibility of applying nonlinear optical organic materials to a high speed optical Kerr shutter was investigated. As switching materials, we chose doped PMMA, in which 2, 5-dichloroterephthal-bis [(p-diethylamino) aniline] (SBAC, Symmetrically substituted Benzylidene Aniline) dyes with large χ values were dispersed. The solubilities of the SBAC dyes were increased by controlling their polarity and bulkiness. As the dye concentration was increased, the χ of the doped PMMA increased to as large as 2.61013 esu. In addition, the extinction ratio of the doped PMMA, an important factor in Kerr shutter operation, was improved to 45 dB by investigating polymerization conditions and processes. As a result, optical Kerr shutter operation was observed in a doped polymer system for the first time, and the n2 value of doped PMMA with a χ value of 1.51013 esu was found to be 9.11015 cm2W1.

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.

This paper describes the performance analysis of a distributed antenna system which includes space and path diversity with radio channel estimation. This system is used for CDMA personal communication systems. In this paper, the performance of a diversity system is analyzed precisely considering multipath and inter-antenna interference. In a diversity system, the adaptive RAKE receiver which estimates the characteristics of a radio channel adaptively has been used for diversity combining. In the adaptive RAKE, the time-variant characteristic has been approximated by a time function. In this paper, the estimation performance of the adaptive RAKE is analyzed in cases of time functions of 0-th, first and second degrees. The performances are evaluated and compared with the differential RAKE. The adaptive RAKE is found to improve the signal quality of more than 2dB in comparison with the differential RAKE. It is also found that the optimum parameter design can be achieved flexibly for radio channel estimation by using higher degree time functions.

The blocking probabilities of n64Kb/s multi-slot calls are generally much higher than that of single slot calls. In order to improve these blocking probabilities of multi-slot calls, we propose a scheme to limit the number of time slots to be searched for lower rate calls. We analyze the performance of our scheme in a double-buffered time-space-time switching network which accommodates multi-slot calls as well as single-slot calls. The proposed method yields the reduced blocking probabilities of multi-slot calls, the increased traffic handling capacity and the reduced CPU processing load, compared with those of the conventional methods.

We report the dispersion of two-photon absorption (TPA) coefficient, (β), in polydiacetylene (12, 8) thin film waveguides in the wavelength range less than the one-photon band-gap with a 100 femtosecond mode-locked Ti: Sapphire laser pulses. The TPA coefficient was found to be 4 cm/GW for TE polarization at 900 nm (1.38 eV) by taking into account a Gaussian intensity distribution as well as a temporal pulse shape. We observed a sharp resonance in β above the first one-photon allowed transition with a full width at half maximum (FWHM) of 90 meV.

Optical Kerr effect were applied to all-optical switching devices in the form of nonlinear waveguide directional couplers. The nonlinear waveguide directional coupler consists of a quartz thin gap between two Corning 7059 guided layers on a pyrex substrate with ion-milled grating and organic thin film as a top layer. The vacuum-deposited polydiacetylene (12, 8) film was used as an organic nonlinear material. Power-dependent switching phenomenon in this asymmetrical nonlinear directional coupler was observed by 100 fs pulse duration of mode-locked Ti: Sapphire laser.

Recent progress on the ultrahigh-speed optical transmission experiments are reviewed including the ultrashort pulse generation, high-speed timing extraction, all-optical multi/demultiplexing. Also discussed are the latest 100 Gbit/s experiments and a scope to higher bit-rate, longer distance optical transmission.

Cone and Block methods that sharply reduce logic simulation time in E-beam guided-probe diagnosis are proposed. These methods are based on a primitive-cell-level tracing algorithm, which traces faulty-state cells one by one in the primitive-cell level. By executing logic simulations in these methods so that simulated responses are reported only for the small set of nodes in a tracing path and in the immediate vicinity, simulation CPU time is sharply reduced with state-of-the-art logic simulators such as the Verilog-XL. With the proposed methods, the total CPU time in a diagnostic process can be reduced to 1/700 that of a conventional method. Additionally, the total amount of simulation date also reduces to 1/40 of its original amount. These methods were applied to the guided-probe diagnosis of actual 110k-gate ASIC chips and it was verified that they could be diagnosed in under seven hours per device, which is practical. This technology will greatly contribute to shortening the turnaround time of ASIC development.

This paper uses both network analysis and experiments to confirm that the neural network learning algorithm that minimizes output variation (BPV) provides much more robustness than back-propagation (BP) or BP with noise-modified training samples (BPN). Network analysis clarifies the relationship between sample displacement and what and how the network learns. Sample displacement generates variation in the output of the output units in the output layer. The output variation model introduces two types of deformation error, both of which modify the mean square error. We propose a new error which combines the two types of deformation error. The network analysis using this new error considers that BPV learns two types of training samples where the modification is either towards or away from the category mean, which is defined as the center of sample distribution. The magnitude of modification depends on the position of the training sample in the sample distribution and the degree of leaning completion. The conclusions is that BPV learns samples modified towards to the category mean more stronger than those modified away from the category mean, namely it achieves nonuniform learning. Another conclusion is that BPN learns from uniformly modified samples. The conjecture that BPV is much more robust than the other two algorithms is made. Experiments that evaluate robustness are performed from two kinds of viewpoints: overall robustness and specific robustness. Benchmark studies using distorted handprinted Kanji character patterns examine overall robustness and two specifically modified samples (noise-modified samples and directionally-modified samples) examine specific robustness. Both sets of studies confirm the superiority of BPV and the accuracy of the conjecture.

The Alopex algorithm is presented as a universal learning algorithm for neural networks. Alopex is a stochastic parallel process which has been previously applied in the theory of perception. It has also been applied to several nonlinear optimization problems such as the Travelling Salesman Problem. It estimates the weight changes by using only a scalar cost function which is measure of global performance. In this paper we describe the use of Alopex algorithm for solving nonlinear learning tasks by multilayer feed-forward networks. Alopex has several advantages such as, ability to escape from local minima, rapid algorithmic computation based on a scalar cost function and synchronous updation of weights. We present the results of computer simulations for several tasks, such as learning of parity, encoder problems and the MONK's problems. The learning performance as well as the generalization capacity of the Alopex algorithm are compared with those of the backpropagation procedure, and it is shown that the Alopex has specific advantages over backpropagation. An important advantage of the Alopex algorithm is its ability to extract information from noisy data. We investigate the efficacy of the algorithm for faster convergence by considering different error functions. We show that an information theoretic error measure shows better convergence characteristics. The algorithm has also been applied to more complex practical problems such as undersea target recognition from sonar returns and adaptive control of dynamical systems and the results are discussed.

Recently, the back propagation method, which is one of the algorithms for learning neural networks, has been widely applied to various fields because of its excellent characteristics. But it has drawbacks, for example, slowness of learning speed, the possibility of falling into a local minimum and the necessity of adjusting a learning constant in every application. In this article we propose an algorithm which overcomes some of the drawbacks of the back propagation by using an improved genetic algorithm.