In this paper, we are concerned in obtaining multicast trees in packet-switched networks such as ATM nets, when there exist constraints on the packet (cell)-replication capabilities of the individual switching nodes. This problem can be formulated as the Steiner tree problem with degree bounds on the nodes, so we call it the Degree-Constrained Steiner Tree problem (DCST). Four heuristic algorithms are proposed: the first is a combined version of two well-known Steiner tree algorithms, heuristic Naive and the shortest path heuristic (SPH), and the second is a relaxation algorithm based on a mathematical formulation of the DCST, and the last two use a tree reconfiguration scheme based on the concept of 'logical link. ' We experimentally compare our algorithms with the previous ones in three respects; number of solved instances, objective value or tree cost, and computation time. The experimental results show that there are few instances unsolved by our algorithms, and the objective values are mostly within 5% of optimal. Computation times are also acceptable.

A high quality speech synthesis technique based on the wavelet subband analysis of speech signals was newly devised for enhancing the naturalness of synthesized voiced consonant speech. The technique reproduces a speech characteristic of voiced consonant speech that shows unvoiced feature remarkably in the high frequency subbands. For mixing appropriately the unvoiced feature into voiced speech, a noise inclusion procedure that employed the discrete wavelet transform was proposed. This paper also describes a developed speech synthesizer that employs several random fractal techniques. These techniques were employed for enhancing especially the naturalness of synthesized purely voiced speech. Three types of fluctuations, (1) pitch period fluctuation, (2) amplitude fluctuation, and (3) waveform fluctuation were treated in the speech synthesizer. In addition, instead of a normal impulse train, a triangular pulse was used as a simple model for the glottal excitation pulse. For the compensation for the degraded frequency characteristic of the triangular pulse that overdecreases than the spectral -6 dB/oct characteristic required for the glottal excitation pulse, the random fractal interpolation technique was applied. In order to evaluate the developed speech synthesis system, psychoacoustic experiments were carried out. The experiments especially focused on how the mixed excitation scheme effectively contributed to enhancing the naturalness of voiced consonant speech. In spite that the proposed techniques were just a little modification for enhancing the conventional LPC (linear predictive coding) speech synthesizer, the subjective evaluation suggested that the system could effectively gain the naturalness of the synthesized speech that tended to degrade in the conventional LPC speech synthesis scheme.

In this paper, we present a numerical method with guaranteed accuracy to solve initial value problems (IVPs) of normal form simultaneous first order ordinary differential equations (ODEs) which have wide domain. Our method is based on the algorithm proposed by Kashiwagi, by which we can obtain inclusions of exact values at several discrete points of the solution curve of ODEs. The method can be regarded as an extension of the Lohner's method. But the algorithm is not efficient for equations which have wide domain, because the error bounds become too wide from a practical point of view. Our purpose is to produce tight bounds even for such equations. We realize it by combining Kashiwagi's algorithm with the mean value form. We also consider the wrapping effects to obtain tighter bounds.

New equivalent characterizations are derived for Schur stability property of real polynomials. They involve a single scalar parameter, which can be regarded as a freedom incorporated in the given polynomials so long as the stability is concerned. Possible applications of the expressions are suggested to the latest results for stability robustness analysis in parameter space. Further, an extension of the characterizations is made to the matrix case, yielding one-parameter expressions of Schur matrices.

ATM networks are connection-oriented. Making a call requires first sending a message to do an admission control to guarantee the connections' QoS (quality of service) in the network. In this paper, we focus on the problem of translating a global QoS requirement into a set of local QoS requirements in ATM networks. Usually, an end-user is only concerned with the QoS requirements on end-to-end basis and does not care about the local switching node QoS. Most of recent research efforts only focus on worst-case end-to-end delay bound but pay no attention to the problem of distributing the end-to-end delay bound to local switching node. After admission control, when the new connection is admitted to enter the network, they equally allocate the excess delay and reserve the same bandwidth at each switch along the path. But, this can not improve network utilization efficiently. It motivates us to design a novel local QoS requirement allocation scheme to get better performance. Using the number of maximum supportable connections as the performance index, we derive an optimal delay allocation (OPT) policy. In addition, we also proposed an analysis model to evaluate the proposed allocation scheme and equal allocation (EQ) scheme in a series of switching nodes with the Rate-controlled scheduling architecture, including a traffic shaper and a non-preemptive earliest-deadline-first scheduler. From the numerical results, we have shown the importance of allocation policy and explored the factors that affect the performance index.

In this paper, an attempt was made to evaluate mental workload using chaotic analysis of EEG. EEG signals registered from Fz and Cz during a mental task (mental addition) were recorded and analyzed using attractor plots, fractal dimensions, and Lyapunov exponents in order to clarify chaotic dynamics and to investigate whether mental workload can be assessed using these chaotic measures. The largest Lyapunov exponent for all experimental conditions took positive values, which indicated chaotic dynamics in the EEG signals. However, we could not evaluate mental workload using the largest Lyapunov exponent or attractor plot. The fractal dimension, on the other hand, tended to increase with the work level. We concluded that the fractal dimension might be used to evaluate a mental state, especially a mental workload induced by mental task loading.

Detection of nonlinearly distorted signals is an essential problem in telecommunications. Recently, neural network combined conventional equalizer has been used to improve the performance especially in compensating for nonlinear distortions. In this paper, the self-organizing map (SOM) combined with the conventional symbol-by-symbol detector is used as an adaptive detector after the output of the decision feedback equalizer (DFE), which updates the decision levels to follow up the nonlinear distortions. In the proposed scheme, we use the box distance to define the neighborhood of the winning neuron of the SOM algorithm. The error performance has been investigated in both 16 QAM and 64 QAM systems with nonlinear distortions. Simulation results have shown that the system performance is remarkably improved by using SOM detector compared with the conventional DFE scheme.

In this article, we survey current and next generation IX (Internet eXchange) technologies. An IX is a mechanism to interconnect many networks to each other. In other words, an ISP can establish 'peerings' with other ISPs by connecting their routers into IXes. First, we describe the basic IX model, including a policy model, called the 'bilateral' model, which allows participating ISPs to control routing policy and traffic on a 'peer' basis. Next, we classify current IX architectures from a technical point of view and discuss issues of current IXes. In the latter potion of this article, we describe next generation IX technologies, which achieve new features for IXes, such as: enabling larger volume traffic exchange with optical technology, providing virtual private peerings, migrating data-link media to participate into an IX, and exchanging traffic over widely distributed areas. We survey cutting-edge technologies for next generation IXes, and discuss the future of IX technology.

Recently, the Guaranteed Frame Rate (GFR) service was proposed as a new service category of ATM to support non-realtime data applications and to provide the minimum rate guarantee. To keep the simplicity of GFR as much as possible and overcome defects of FIFO-based mechanisms, we propose a FIFO-based algorithm extending DFBA one to improve the fairness and provide the minimum rate guarantee for a wider range of Minimum Cell Rate (MCR). The key idea is controlling the number of CLP1 cells which are occupying more buffer space than the fair share even when the queue length is below Low Buffer Occupancy (LBO).

This paper provides a new robust guaranteed cost controller design method for discrete parameter uncertain time delay systems. The result shows much tighter bound of guaranteed cost than that of existing paper. In order to get the optimal (minimum) value of guaranteed cost, an optimization problem is given by linear matrix inequality (LMI) technique. Also, the parameter uncertain systems with time delays in both state and control input are considered.

In [3], the decision feedback channel estimation (DFCE) for M-ary orthogonal modulation in direct sequence/code division multiple access (DS/CDMA) systems was proposed. However, the performance of the DFCE in the multiuser environment is severely degraded due to multiple access interference (MAI). In this letter, to overcome this problem, we modify the DFCE as multistage configurations using a multistage parallel interference cancellation (PIC) scheme. According to the results of our simulations, the performance of coherent demodulation using the proposed multistage DFCE is significantly improved in comparison with conventional demodulation in [3].

Emerging multimedia technologies introduce the prevalent multicast transmission, and the multicast tree is determined using the time-invariant network parameters. This paper addresses the time-varying multicast tree problem and presents path selection heuristics for multicast routing to determine an alternative path for real-time applications. A network is partitioned into the optimal region, the disjoint region, and the edge cutset if a branch of the multicast tree meets the un-guaranteed QoS condition. The path selection heuristics operate during the multicast session phase to efficiently select an alternative routing path containing an edge in the edge cutset to connect the multicast tree again. The source-based heuristics PS-SPT finds the path for minimal source-to-destination delay and the sharing-based heuristics PS-DDMC for minimal total cost. These path selection heuristics can efficiently provide solutions to keep the multicast transmission reliable. Simulation results also show that the proposed heuristics can provide effective good solutions for real-time multicast transmission. PS-SPT can select a path with optimal source-to-destination delay and PS-DDMC can select a path with optimal total cost.

This paper proposes a receiver antenna weight-updating algorithm using I/Q-code multiplexed pilot and decision feedback data symbols after channel decoding for both reference signal generation of the mean squared error (MSE) calculation and channel estimation (also for Rake combining) in the coherent adaptive antenna array diversity (CAAAD) receiver and investigates its performance, in order to decrease further the transmit power of a mobie station, thereby increasing system capacity in the wideband direct sequence code division multiple access (W-CDMA) reverse link. Experimental results show that the required transmit Eb/N0 for the average BER of 10-3 with the CAAAD receiver using pilot and decision feedback data symbols after channel decoding both for reference signal generation and for channel estimation can be decreased by approximately 0.8 dB compared to when using only pilot symbols with convolutional coding or turbo coding, when the ratio of the target Eb/I0 for fast transmit power control of the desired to interfering users is Δ Eb/I0 = -12 dB. The results also elucidate that the required transmit Eb/N0 at the average BER of 10-6 with turbo coding using the proposed decision feedback antenna weight-updating and channel estimation is smaller by approximately 0.5 dB than that using convolutional coding when the channel interleaving length is 20 msec for Δ Eb/I0 = -12 dB.

EMI coupling paths in an electronic controller are investigated experimentally. Common-mode current measurements on the attached cable are used for diagnosing changes made to the EMI coupling path. Experiments that include shielding various portions of the PCB, and re-routing high-speed traces are conducted to characterize the coupling path. A means of identifying and characterizing EMI coupling paths in functioning hardware, and relating them to design features, is demonstrated.

In this paper, we present an image compression algorithm using two concepts, subdividing an image matrix and stratifying submatrices into FD-submatrices (feature distribution submatrices). According to the feature distribution and the view that an image can be decomposed into some feature layers, we generate a compression tree by setting up a logic process of decomposition and stratification. To get better compression ratios, the set of submatrices having one and zero as elements, including logic flag sequences is compressed by vector space theory.

This paper elucidates the most appropriate hybrid automatic-repeat-request (ARQ) scheme, i.e., which can achieve the highest throughput, for high-speed packet transmission in the W-CDMA forward link by comparing the throughput performance of three types of hybrid ARQ schemes: type-I hybrid ARQ with packet combining (PC), type-II hybrid ARQ, and basic type-I hybrid ARQ as a reference. Moreover, from the viewpoint of maximum throughput, the respective optimum roles of ARQ and channel coding in hybrid ARQ are also clarified, such as the optimum coding rate and the packet length related to the interleaving effect. The simulation results reveal that the type-II scheme exhibits the best throughput performance, and the required received signal energy per chip-to-background noise spectral density ratio (Ec/N0) at the throughput efficiency of 0.2/0.4/0.6 is improved by 0.7/0.3/0.1 dB and 3.9/1.8/0.5 dB, respectively, compared to the type-I scheme with and without PC in a 2-path Rayleigh fading channel with the average equal power at the maximum Doppler frequency of 5 Hz and the packet length of 4 slots (= 0.667 4 = 2.667 msec). However, the improvement of the type-II scheme compared to the type-I scheme with PC is small or the achievable throughput is almost identical in the high-received Ec/N0 region. On the other hand, the type-I scheme with PC is much less complex and thus preferable, while maintaining almost the same throughput performance or allowing very minor degradation compared to that with type-II. The results also elucidate that, while the optimum coding rate depends on the required throughput in the basic type-I and type-I with PC schemes, it is around between 3/4 and 8/9 in type-II, resulting in a higher throughput efficiency. In addition, for high-speed packet transmission employing a hybrid ARQ scheme, a shorter retransmission unit size is preferable such as 1 slot, and the fast transmit power control is effective only under conditions such as a low maximum Doppler frequency and a high transmit Ec/N0 region.

A new approach for extracting significant characteristic within speech signal for distinct speaker is presented. Based on the multiresolution property of wavelet transform, quadrature mirror filters (QMFs) derived by Daubechies is used to decompose the input signal into varied frequency channels. Owning to the uncorrelation property of each resolution derived from QMFs, Linear Predict Coding Cepstrum (LPCC) of lower frequency region and entropy information of higher frequency region for each decomposition process are calculated as the speech feature vectors. In addition, a hard thresholding technique for lower resolution in each decomposition process is also used to remove the effect of noise interference. The experimental result shows that by using this mechanism, not only effectively reduce the effect of noise inference but improve the recognition rate. The proposed feature extraction algorithm is evaluated on MAT telephone speech database for Text-Independent speaker identification using vector quantization (VQ). Some popular existing methods are also evaluated for comparison in this paper. Experimental results show that the performance of the proposed method is more effective and robust than that of the other existing methods. For 80 speakers and 2 seconds utterance, the identification rate is 98.52%. In addition, the performance of our method is very satisfactory even at low SNR.

It is very difficult to obtain a linearizing feedback and a coordinate transformation map, even though the system is feedback linearizable. It is known that finding a desired transformation map and feedback is equivalent to finding an integrating factor for an annihilating one-form. In this paper we develop a numerical algorithm for an integrating factor involving a set of partial differential equations and corresponding zero-form using the C.I.R method. We employ a tensor product splines as an interpolation method to data which are resulted from the numerical algorithm in order to obtain an approximate integrating factor and a zero-form in closed forms. Next, we obtain a coordinate transformation map using the approximate integrating factor and zero-form. Finally, we construct a stabilizing controller based on a linearized system with the approximate coordinate transformation.

In this paper we propose a learning algorithm to enhance the fault tolerance of feedforward neural networks (NNs for short) by manipulating the gradient of sigmoid activation function of the neuron. We assume stuck-at-0 and stuck-at-1 faults of the connection link. For the output layer, we employ the function with the relatively gentle gradient to enhance its fault tolerance. For enhancing the fault tolerance of hidden layer, we steepen the gradient of function after convergence. The experimental results for a character recognition problem show that our NN is superior in fault tolerance, learning cycles and learning time to other NNs trained with the algorithms employing fault injection, forcible weight limit and the calculation of relevance of each weight to the output error. Besides the gradient manipulation incorporated in our algorithm never spoils the generalization ability.

In this paper, we propose an adaptive video frame rate control method, called AFCON, that video encoders use in conjunction with explicit rate based congestion control in the network. First, an encoder buffer constraint which guarantees the end-to-end delay of video frames is derived under the assumption of bounded network transmission delay for every frame data. AFCON is based on the constraint and consists of future channel rate prediction, frame discarding, and frame skipping. Recursive Least-Squares (RLS) is used to predict the low-frequency component of the channel rate. Frame discarding prevents the delay violation of frames due to the prediction error of the channel rate. Frame skipping adapts the encoder output rate to the channel rate while avoiding abrupt quality degradation during the congestion period. From the simulation results, it is shown that AFCON can adapt to the time-varying rate channel with less degradation in temporal resolution and in PSNR performance compared to the conventional approach.