In this paper we study the scalability issue in the design of a centralized bandwidth broker model for dynamic control and management of QoS provisioning. We propose and develop a path-oriented, quota-based dynamic bandwidth allocation mechanism for efficient admission control operations under the centralized bandwidth broker model. We demonstrate that this dynamic bandwidth allocation mechanism can significantly reduce the overall number of QoS state accesses/updates, thereby increasing the overall call processing capability of the bandwidth broker. Based on the proposed dynamic bandwidth allocation mechanism, we also extend the centralized architecture with a single bandwidth broker to a hierarchically distributed architecture with multiple bandwidth brokers to further improve its scalability. Our study demonstrates that the bandwidth broker architecture can be designed in such a manner that it scales with the increase in the network capacity.

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.

In this paper, we propose an ECG waveform compression technique based on the matching pursuit. The matching pursuit is an iterative non-orthogonal signal expansion technique. A signal is decomposed to atoms in a function dictionary. The constraint to the dictionary is only the over-completeness to signals. The function dictionary can be defined to be best match to the structure of the ECG waveform. In this paper, we introduce the multiscale analysis to the implementation of inner product computations between signals and atoms in the matching pursuit iteration. The computational cost can be reduced by utilization of the filter bank of the multiscale analysis. We show the waveform approximation capability of the matching pursuit with multiscale analysis. We show that a simple 4-tap integer filter bank is enough to the approximation and compression of ECG waveforms. In ECG waveform compression, we apply the error feed-back procedure to the matching pursuit iteration to reduce the norm of the approximation error. Finally, actual ECG waveform compression by the proposed method are demonstrated. The proposed method achieve the compression by the factor 10 to 30. The compression ratio given by the proposed method is higher than the orthogonal wavelet transform coding in the range of the reconstruction precision lower than 9% in PRD.

In this paper, a CMOS down-conversion double-balanced mixer is presented with the modified low voltage design technique. The frequencies of the radio frequency (RF) signal, local oscillator (LO) and intermediate frequency (IF) are 2.4 GHz, 2.3 GHz and 100 MHz, respectively. Measurement results of the proposed mixer exhibit 6.7 dB of conversion gain, -18 dBm of input 1 dB compression point (P-1 dB), -8 dBm of input-referred third-order intercept point (IIP3), and 14.7 dB single-side band (SSB) noise figure (NF) while applying -8 dBm LO power and consumes 3.3 mA from 1.8 V supply voltage. It can provide 0.7 dB conversion gain when the supply voltage reduces to 1.3 V. This mixer was fabricated in a 0.35 µm 1P4M standard digital CMOS process and the die size is 1.5 1.1 mm2.

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.

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].

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.

A simple embedded lossless wavelet-based image coding algorithm called Successive Partition Zero Coder (SPZC), which uses hybrid bit scanning and non-causal adaptive context modelling, is proposed. By successive partition the wavelet coefficients in the spatial-frequency domain, the coefficients are ordered based on their absolute range. The prioritized coefficients are quantized in a successive approximation manner to generate a binary sequence, which is divided into subsources and encoded by arithmetic coder with non-causal adaptive context modelling. This method is suited for progressive image transmission (PIT). Experimental results show that SPZC outperforms other state-of-the-art coders such as SPIHT, CREW and LJPEG, but slightly inferior to ECECOW and CALIC in lossless mode. SPZC is simple in both context modelling and implementation.

This paper discusses recognition up to intensities of mix of primary facial expressions in real time. The proposed recognition method is compatible with the MPEG-4 high level expression Facial Animation Parameter (FAP). In our method, the whole facial image is considered as a single pattern without any block segmentation. As model features, an expression vector, viz. low global frequency coefficient (DCT) changes relative to neutral facial image of a person is used. These features are robust and good enough to deal with real time processing. To construct a person specific model, apex images of primary facial expression categories are utilized as references. Personal facial expression space (PFES) is constructed by using multidimensional scaling. PFES with its generalization capability maps an unknown input image relative to known reference images. As PFES possesses linear mapping characteristics, MPEG-4 high level expression FAP can be easily calculated by the location of the input face on PFES. Also, temporal variations of facial expressions can be seen on PFES as trajectories. Experimental results are shown to demonstrate the effectiveness of the proposed method.

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.

An unwrapping of signal coefficients in transform domain is proposed for applications in which a lossy operation is performed on the coefficients between analysis and synthesis. It is shown that the unwrapping-based modification of signal-to-additive-signal ratio can employ the fact that an implementation of a biorthogonal decomposition is characterized by a mutually orthogonal eigenvectors. An example to illustrate the benefits of the presented approach in lossy image compression applications is shown.

This letter presents a method for reducing power dissipation in a protocol converter. The communication protocol of a VLSI chip hierarchically consists of several sub-protocols and only one of them can be actively working at any given time. In general, protocol converters are implemented by dual protocols of the initially given protocols which are to be interfaced. If the duals of those sub-protocols are implemented in separate modules, we can separate active modules and inactive modules on the fly since only one of the modules can be active at a time. The active/inactive state of a module can be monitored by the control signals that represent the execution of the protocol corresponding to the module. Power reduction can be achieved by dynamically suppressing the clock supply to inactive modules. To trade-off the power reduction rate against the area overhead, the module granularity must be properly chosen. For this purpose, we implement the duals of the atomic protocols in the same module if their state graphs share states except the initial state. Our experimental results show that this method provides significant savings in power consumption of between 18.4% and 92.1% with a 5.3% area overhead.

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 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.

This paper compares the path detection probability for Rake combining and the BER performance of packet transmission with the length of TPKT = 10 (20) msec using the coherent adaptive antenna array diversity (CAAAD) receiver with those using a multi-beam receiver employing fixed antenna weights both with four antennas in a multipath fading channel in the W-CDMA reverse link. Laboratory experimental results elucidate that the required average received signal energy per bit-to-background noise spectrum density (Eb/N0) at the detection probability of 90% of at least one path and of two paths for the fading maximum Doppler frequency of fD = 5 (80) Hz using a multi-beam receiver with the number of beams equal to NBeam = 12 was decreased by approximately 1.0 (1.0) dB and 2.0 (2.0) dB, respectively, compared to that using the CAAAD receiver with the step size of µ= 10-2 for the average received SIR of the desired user of -12 dB in a 2-path Rayleigh fading channel with average equal power in a 5-user environment. We also found that the required average received Eb/N0 at the average BER of 10-3 using the multi-beam receiver was decreased by approximately 5.0 (2.5) dB compared to that of the CAAAD receiver with µ= 10-2, and the loss of the required average received Eb/N0 compared to that of CAAAD with sufficiently converged receiver antenna weights was approximately 2.0 (1.0) dB for TPKT = 10 (20) msec when the average received SIR = -12 dB in a 5-user environment.

This paper proposes a novel adaptive array configuration that reduces high-power co-channel interference (CCI) by utilizing the difference in arrival times between CCI and the desired signal in asynchronous TDD systems. The proposed adaptive array extracts only the CCI and employs pre-null steering for only the CCI by utilizing the fact that only the CCI arrives during the guard time in asynchronous TDD systems. Since the proposed adaptive array enables us to apply the Minimum Mean Square Error (MMSE) algorithm through synchronization with the desired signal using the output signal obtained by pre-null steering, high quality transmission can be achieved even in the presence of high-power CCI. Moreover, based on measurements using a fading simulator and field data, an adaptive array testbed exemplifying the proposed configuration is presented to show the reduction in the high-power CCI.

Most of the previous controllers proposed for output regulation problems on uncertain nonlinear systems tried to keep the state variables to the nominal equilibrium points. In this letter, however, the dynamic state feedback controller makes the state variables follow the perturbed equilibrium points computed from an equilibrium-estimator.

Currently, the most popular model in data compression theory is that of stationary ergodic sources. But there do exist sequences each of which is not emitted from any stationary ergodic source but can be compressed sufficiently by a certain algorithm. We estimate the size of the set of such sequences in terms of Hausdorff dimension.

We propose a novel control method for an unknown distributed system, and apply it to transmission power control in a code-division multiple access (CDMA) wireless system. Our proposed distributed control contains conventional transmission power control and packet transmission rate control for constant bit rate (CBR) and transmission control protocol (TCP) connections. Using theoretical analysis and computer simulations we show that our method for transmission power control allows high bandwidth utilization for both CBR and TCP connections, and that conventional power control, by contrast, does not make efficient use of bandwidth in TCP connections.

In this paper, we survey the fairness issues in the congestion control mechanisms of TCP, which is one of most important service aspects in the current and future Internet. We first summarize the problems from a perspective of the fair service among connections. Several solution methods are next surveyed. Those are modifications of TCP congestion control mechanism and router support for achieving the fair service among TCP connections. We finally investigate the fair share of resources at endhosts.