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.

In the past, a number of scheduling algorithms that approximate GPS, such as WFQ, have been proposed and have received much attention. This class of algorithms provides per-flow QoS guarantees in terms of the bounded delay and minimum bandwidth guarantee. However, with O(log N) computational cost for each new arrival scheduling, where N is the number of backlogged flows, these algorithms are expensive to implement (e.g., in terms of scalability). Moreover, none of them addresses the issues of delay distribution and jitter. In this paper, we propose a new traffic scheduling discipline called Jitter Control Frame-based Queueing (JCFQ) that provides an upper bound for delay jitter in the case of rate-controlled connections, such as packet video streams and IP telephony, while guaranteeing bounded delay and worst-case fair weighted fairness, such as in the WF2Q algorithm, but with O(1) complexity in selecting the next packet to serve, assuming that the number of flows is fixed. Three different algorithms for slot or service order assignment between flows are proposed: Earliest Jitter Deadline First (EJDF), Rate Monotonic (RM) and Maximum Jitter First (MJF). In these algorithms, delay jitter is formulated into the virtual finish time calculation. We compare the fairness, delay and jitter performance of the JCFQ with that of the MJF algorithm with WF2Q via simulation. The results show that with proper choice of the slot size, JCFQ can achieve better flow isolation in delay distribution than can WF2Q.

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).

As a method of analyzing the wave scattering from a finite periodic surface, this paper introduces a periodic approach. The approach first considers the wave diffraction by a periodic surface that is a superposition of surface profiles generated by displacing the finite periodic surface by every integer multiple of the period . It is pointed out that the Floquet solution for such a periodic case becomes an integral representation of the scattered field from the finite periodic surface when the period goes to infinity. A mathematical relation estimating the scattering amplitude for the finite periodic surface from the diffraction amplitude for the periodic surface is proposed. From some numerical examples, it is concluded that the scattering cross section for the finite periodic surface can be well estimated from the diffraction amplitude for a sufficiently large .

In this paper, we explore the possibility of applying associative memories for locating frontal views of human faces in complex scenes. An appealing property of the associative-memory-based face detection system is that learning of the associative memory may be achieved by using a simple Hebbian learning rule. In addition, a simple heuristic rule is used to quickly filter a certain amount of nonface images at the very beginning of the whole detection procedure. By using the rule, we won't waste unnecessary computational resources on those nonface images. A database consisting of 74 images was used to test the performance of our associative-memory-based human face detection system.

Mobile communication channels always suffer serious frequency-selective fading due to multipath effect. Traditional spreading codes are characterized by the fact that their time-domain orthogonality is based on fixed chip width across a code period. They often fail to perform well under frequency-selective fading. This paper proposes a new class of CDMA codes, wavelet-packet orthogonal codes capable to retain time-domain orthogonality as well as to offer intra-code subband diversity to mitigate frequency-selective fading. The new codes are constructed by congregating several wavelets with various dilations and shifts. The combination of the wavelets in different nodes in a wavelet-packet full binary tree enables frequency diversity capability. Owing to the even code length, they can be easily used in mobile communications for multi-rate streaming and multi-code spreading. The performance study is carried out using correlation statistics distribution convolution algorithm and the results reveal that wavelet-packet codes, combined with RAKE receiver, perform better than traditional spreading codes in frequency-selective fading channels.

Fairness as defined in wireline network cannot be achieved in wireless packet networks due to the bursty and location-dependent channel errors of wireless link. Channel-state dependent scheduling and compensation mechanism for errored flows are generally employed to improve the fairness in wireless packet scheduling algorithms. Most of the wireless scheduling algorithms, however, have two common significant problems. One problem is that they operate incorrectly unless all flows have the same packet size. This is due to the incorrect lead-and-lag model and the swapping-based rough compensation mechanism of the algorithms. The other problem is the degradation of error-free flow during compensation. The root of the degradation is that the bandwidth for compensation cannot be reserved since it is very difficult to predict. In this paper, we introduce WGPS (Wireless General Processor Sharing) to define fairness in wireless networks and present PWGPS as a packetized algorithm of WGPS. In our method, lead and lag of all flows are defined in terms of virtual time which is flexible enough to deal with packet size differences. Further, compensation is done by increasing the service share of the errored flow to a predetermined amount Δ. This enables the maximum bandwidth for compensation can be estimated and thus reserved. Our method can be proved to achieve improved fairness as compared with the previous scheduling algorithms.

This paper discusses an application of fingerprint identification technology to enhanced human-machine interaction, and also to information systems, specifically to a mobile authentication terminal for secure networked services and to digital appliances. A "Fingerprint User Interface (FpUI)," exploits information regarding not only who put a finger on its sensor but which specific finger it was. With this user-friendly interface, a user can assign commands, data objects, status, or personalized settings to individual fingers. A functional architecture for a mobile authentication terminal, "Pocket-PID," with fingerprint identification capability is proposed which features an easy-to-use FpUI and high security, where the identification function is totally enclosed within the unit. This enables a user's identity authenticated without any possibility of actual fingerprint data being disclosed. The Pocket-PID facilitates implementation of networked services based on secure biometric user identification.

In this paper we propose an integration of face identification and facial expression recognition. A face is modeled as a graph where the nodes represent facial feature points. This model is used for automatic face and facial feature point detection, and facial feature points tracked by applying flexible feature matching. Face identification is performed by comparing the graphs representing the input face image with individual face models. Facial expression is modeled by finding the relationship between the motion of facial feature points and expression change. Individual and average expression models are generated and then used to identify facial expressions under appropriate categories and the degree of expression changes. The expression model used for facial expression recognition is chosen by the results of face identification.

This paper proposes a beam and null simultaneous steering Space-Time Equalizer (S/T-Equalizer). The proposed S/T-Equalizer performs separated S/T-signal processing in order to reduce computational complexity to a practical level. For spatial signal processing, a new Adaptive Array Antenna algorithm is used that combines the beam and null steering concepts. For temporal signal processing, a conventional delayed decision feedback sequence estimation equalizer may be used. The proposed S/T-Equalizer was prototyped, and a series of field tests was conducted using a 5 GHz frequency band to evaluate transmission performances of the proposed system. Results show that the proposed S/T-Equalizer can reduce inter-symbol interference effects while maintaining reasonable signal strength, thereby improving BER performance.

Using moment generating function (MGF) of generalized selection combining (GSC) output signal-to-noise ratio (SNR), we derive closed-form expressions for average combined SNR at the output of GSC, which optimally combines the N largest out of L available diversity signals, over Nakagami-m fading channels for N = 2, 3 and L = 4. The Nakagami-m fading statistics on each diversity branch are assumed to be independent and identically distributed (i.i.d.). The average combined SNRs at the outputs of GSC receivers are also compared with the average combined SNRs at the outputs of conventional maximal ratio combining (MRC) and selection combining (SC).

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.

This paper proposes the person authentication scheme with the images of his or her face. In the scheme, the CCD camera picks up the images of the person's face casted by the lights from the various directions. The lights can be switched in a random order so fast that you cannot change the forged photographs simultaneously with the switches of the lights. This scheme is then highly secure and has a high cost performance. There are some appropriate applications of the scheme, such as the access control system of entering a room. The security and the efficiency of the scheme is checked by the performance of the false rejection rate and the false acceptance rate.

This paper presents a scale invariant face detection and classification method which uses shift invariant features extracted from a Log-Polar image. Scale changes of a face in an image are represented as shift along the horizontal axis in the Log-Polar image. In order to obtain scale invariant features, shift invariant features are extracted from each row of the Log-Polar image. Autocorrelations, Fourier spectrum, and PARCOR coefficients are used as shift invariant features. These features are then combined with simple classification methods based on Linear Discriminant Analysis to realize scale invariant face detection and classification. The effectiveness of the proposed face detection method is confirmed by experiments using face images captured under different scales, backgrounds, illuminations, and dates. To evaluate the proposed face classification method, we performed experiments using 2,800 face images with 7 scales under 2 different backgrounds and face images of 52 persons.

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.

The diffraction of a plane electromagnetic wave by an impedance wedge whose boundary is described in terms of the skew coordinate systems is treated by using the Wiener-Hopf technique. The problem is formulated in terms of the simultaneous Wiener-Hopf equations, which are then solved by using a factorization and decomposition procedure and introducing appropriate functions to satisfy the edge condition. The exact solution is expressed through the Maliuzhinets functions. By deforming the integration path of the Fourier inverse transform, which expresses the scattered field, the expressions of the reflected field, diffracted field and the surface wave are obtained. The numerical examples for these fields are given and the characteristics of the surface wave are discussed.

This paper proposes a synchronous acquisition method using correlation mapping by multiple-dwell detection considering false alarm penalty in M-ary/SS systems. In the method, first, the correlation value between a received signal and each assigned sequence in an M-ary/SS system in some short duration is calculated for each phase and stored in the mapping. Second, the maximum correlation value of each phase in the mapping is selected and arranged, then, the first probable synchronous phase is decided by the maximum one in these values. Simultaneously, data demodulation starts. Next, to recognize the synchronous phase, i.e., as considering false alarm penalty, the correlation values are calculated in longer duration, and the second probable phase with high reliability can be obtained by suppression of noise to signal level. Finally, if the second synchronous phase is different from the first one, the second one is reset. By this method, a short acquisition time and high reliability of acquisition can be achieved. The improvement of acquisition time and the optimal combination values of dwelling time, which is duration to calculate the correlation, are shown for several conditions in asynchronous M-ary/SSMA.

Linear discriminant analysis (LDA) is a basic tool of pattern recognition, and it is used in extensive fields, e.g. face identification. However, LDA is poor at adaptability since it is a batch type algorithm. To overcome this, new algorithms of online LDA are proposed in the present paper. In face identification task, it is experimentally shown that the new algorithms are about two times faster than the previously proposed algorithm in terms of the number of required examples, while the previous algorithm attains better final performance than the new algorithms after sufficient steps of learning. The meaning of new algorithms are also discussed theoretically, and they are suggested to be corresponding to combination of PCA and Mahalanobis distance.

A new IDDQ testable design method is proposed for static CMOS PLA circuits. A testable PLA circuit of NOR-NOR type is designed using this method. It is shown that all bridging faults in NOR planes of the testable designed PLA circuit can be detected by IDDQ testing with 4 sets of test input vectors. The test input vectors are independent of the logical functions to be realized in the PLA circuit. PLA circuits are designed using this method so that the quiescent supply current generated when they are tested will be zero. Thus, high resolution of IDDQ tests for the PLA circuits can be obtained by using the testable design method. Results of IDDQ tests of PLA circuits designed using this testable design method confirm not that the expected output can be generated from the circuits but that the circuits are fabricated without bridging faults in NOR planes. Since bridging faults often occur in state-of-the-art IC fabrication, the testable design is indispensable for realizing highly reliable logic systems.

In order to make the ATM network fault-tolerant and the network service flexible, a method for the setting up of backup virtual paths (VP's for short) using multiagents is effective with respect to adaptability to change of network resource and user requirements, examples of which are failure of nodes and links and addition of VP's, respectively. In this method, under the assumption that candidates of backup VP's between different pairs of source and destination nodes are given, the optimum backup VP's are obtained by exchanging information among agents autonomously. First, this paper proposes measures for determining backup VP's between different pairs of source and destination nodes. Next, this paper presents simulation results to evaluate the adaptability of the method. The results show that the method efficiently obtains the optimum backup VP's even when the number of backup VP's increases and that different idle time at each destination node enables to shorten the total processing time while keeping complete detection of shared links.