In this study, we propose a multi-layer perceptron with a glial network which is inspired from the features of glias in the brain. All glias in the proposed network generate independent oscillations, and the oscillations propagate through the glial network with attenuation. We apply the proposed network to the two-spiral problem. Computer simulations show that the proposed network gains a better performance than the conventional multi-layer perceptron.

A millimeter-wave termination which is tolerant to the resistance error of the embedded resistive film in a multi-layered LTCC substrate has been developed. The tolerance to the resistance error can be accomplished using two bifurcated strip lines overlapping with the resistive film, whose lengths are different form each other. It has been experimentally demonstrated that the proposed termination configuration is effective to enhance the tolerance to resistance error of the embedded resistive film in the LTCC substrate.

A dominant-mode rectangular cavity antenna design yielding an improved bandwidth is experimentally verified. Simple field theories indicate that extending the aperture height should increase the antenna bandwidth without shifting the operation frequency. Antenna samples built from a 4.4 dielectric constant material produce 3-dB efficiency bandwidths of 15 and 23 percent for the respective cavity height-to-width ratios of 0.5 and 0.75 at 7 GHz.

We present a new method that can represent the reflectance of metallic paints accurately using a two-layer reflectance model with sampled microfacet distribution functions. We model the structure of metallic paints simplified by two layers: a binder surface that follows a microfacet distribution and a sub-layer that also follows a facet distribution. In the sub-layer, the diffuse and the specular reflectance represent color pigments and metallic flakes respectively. We use an iterative method based on the principle of Gauss-Seidel relaxation that stably fits the measured data to our highly non-linear model. We optimize the model by handling the microfacet distribution terms as a piecewise linear non-parametric form in order to increase its degree of freedom. The proposed model is validated by applying it to various metallic paints. The results show that our model has better fitting performance compared to the models used in other studies. Our model provides better accuracy due to the non-parametric terms employed in the model, and also gives efficiency in analyzing the characteristics of metallic paints by the analytical form embedded in the model. The non-parametric terms for the microfacet distribution in our model require densely measured data but not for the entire BRDF(bidirectional reflectance distribution function) domain, so that our method can reduce the burden of data acquisition during measurement. Especially, it becomes efficient for a system that uses a curved-sample based measurement system which allows us to obtain dense data in microfacet domain by a single measurement.

Newly developed multi-layer inductors on GaAs three-dimensional MMICs are presented. We analyzed single-, double-, triple-, and quadruple-layer stacked-type inductors in what may be the first report on inductors on a GaAs MMIC with three or more layers. The performance of single- and multi-layer inductors was measured and calculated by electromagnetic field simulation. The multi-layer inductors produce 2-11 times higher inductance than that of conventional inductors on 2D-MMICs although they are the same size. This means that the proposed multi-layer inductors have smaller areas with the same inductances than those of conventional inductors. We also conducted the first-ever investigation of how performance factors such as parasitic capacitance, Q-factor, and self-resonant frequency are degraded in multi-layer inductors vis-a-vis those of conventional inductors. A microwave amplifier using multi-layer inductors was demonstrated and found to reduce circuit size by 20%.

This paper presents a new multi-layered artificial immune system architecture using the ideas generated from the biological immune system for solving combinatorial optimization problems. The proposed methodology is composed of five layers. After expressing the problem as a suitable representation in the first layer, the search space and the features of the problem are estimated and extracted in the second and third layers, respectively. Through taking advantage of the minimized search space from estimation and the heuristic information from extraction, the antibodies (or solutions) are evolved in the fourth layer and finally the fittest antibody is exported. In order to demonstrate the efficiency of the proposed system, the graph planarization problem is tested. Simulation results based on several benchmark instances show that the proposed algorithm performs better than traditional algorithms.

A strip line broadside hybrid coupler which is tolerant to manufacturing errors in a multi-layered LTCC substrate has been developed. The tolerance to a displacement error and a thickness variation in the multi-layered LTCC substrate can be achieved by using the tandem arrangement of diagonally shifted coupled lines with adjacent ground walls. It has been demonstrated that the coupling deviation from designed characteristics in our proposed hybrid coupler is very small.

A method was developed for automatic recognition of syllable tone types in continuous speech of Mandarin by integrating two techniques, tone nucleus modeling and neural network classifier. The tone nucleus modeling considers a syllable F0 contour as consisting of three parts: onset course, tone nucleus, and offset course. Two courses are transitions from/to neighboring syllable F0 contours, while the tone nucleus is intrinsic part of the F0 contour. By viewing only the tone nucleus, acoustic features less affected by neighboring syllables are obtained. When using the tone nucleus modeling, automatic detection of tone nucleus comes crucial. An improvement was added to the original detection method. Distinctive acoustic features for tone types are not limited to F0 contours. Other prosodic features, such as waveform power and syllable duration, are also useful for tone recognition. Their heterogeneous features are rather difficult to be handled simultaneously in hidden Markov models (HMM), but are easy in neural networks. We adopted multi-layer perceptron (MLP) as a neural network. Tone recognition experiments were conducted for speaker dependent and independent cases. In order to show the effect of integration, experiments were conducted also for two baselines: HMM classifier with tone nucleus modeling, and MLP classifier viewing entire syllable instead of tone nucleus. The integrated method showed 87.1% of tone recognition rate in speaker dependent case, and 80.9% in speaker independent case, which was about 10% relative error reduction as compared to the baselines.

A lightweight and high gain planar antenna for space use is realized with radial waveguide slotted array and honeycomb structure with the weight of 1.16 kg and the diameter of 920.5 mm. The slot coupling is analyzed by method of moments considering the hybrid mode in the multi-layer waveguide structure. The propagation constant of the honeycomb structure is measured and the low-loss property is obtained at the frequency range of 8 GHz. The fabricated RLSA is measured and the reflection is around -10 dB in 8 GHz band. The measured aperture fields agree with the calculation in the radial direction. In the azimuthal direction, on the other hand, the fields show ripples of 6 dB and 60 degree. The gain of 35.9 dBi with the efficiency of 58.7% is obtained at 8.6 GHz.

This paper investigates the prospects and challenges of hierarchical optical path networks. The merits and issues of introducing higher order optical paths are elucidated. State of the art of the key enabling technologies are demonstrated including hierarchical optical cross-connect switch architectures, hierarchical optical path network design algorithms, a newly developed waveband filter, and waveband conversion technologies.

This paper considers optical transport and packet networks and discusses the constraints and solutions in computation of traffic engineering paths. We categorize the constraints into prunable or non-prunable classes. The former involves a simple metric which can be applied for filtering to determine the path. The latter requires a methodic consideration of more complicated network element attributes. An example of this type of constraints is path loss in which the metric can be evaluated only on a path basis, as opposed to simply applying the metric to the link. Another form of non-prunable constraint requires adaptation and common vector operation. Examples are the switching type adaptation and wavelength continuity, respectively. We provide possible solutions to cases with different classes of constraints and address the problem of path computation in support of traffic engineering in multi-layer networks where a set of constrains are concurrently present. The solutions include the application of channel graph and common vector to support switching type adaptation and label continuity, respectively.

Implementing the fast-responding multi-layer service network (MLSN) functionality will allow the IP/MPLS service network logical topology and Optical Virtual Network topology to be reconfigured dynamically according to the traffic pattern on the network. Direct links can be created or removed in the logical IP/MPLS service network topology, when either extra capacity in MLSN core is needed or existing capacity in core is no longer required. Reconfiguring the logical and virtual network topologies constitute a new manner by which Traffic Engineering (TE) can solve or avoid network congestion problems and service degradations. As both IP and optical network layers are involved, this is called Multi-layer Traffic Engineering. We proposed border model based MLSN architecture in [5]. In this paper, we define the realization of Multi-Layer TE functions using Path Computation Element (PCE) for Border model based MLSN. It defines nodal requirements for multi-layer TE. Requirements of communication protocol between PCC (Path Computation Client) and PCE is introduced. It presents Virtual Network Topology (VNT) scenarios and steps involved along with examples for PCE-based VNT reconfiguration triggered by network failure, where VNT is a set of different layer's network resource accumulation.

This paper proposes an advanced hybrid network architecture and a comprehensive network design of the next-generation science information network, called SINET3. Effectively combining layer-1 switches and IP/MPLS routers, the network provides layer-1 end-to-end circuit services as well as IP and Ethernet services and enables flexible resource allocation in response to service demands. The detailed network design focuses on the tangible achievement of providing a wide range of network services, such as multiple layer services, multiple virtual private network services, advanced qualities of service, and layer-1 bandwidth on demand services. It also covers high-availability capabilities and effective resource assignment in the hybrid network. The cost reduction effect of our network architecture is also shown in this paper.

For more efficient data transmissions, a new MLP/BP-based channel equalizer is proposed to compensate for multi-path fading in wireless applications. In this work, for better system performance, we apply the soft output and the soft feedback structure as well as the soft decision channel decoding. Moreover, to improve packet error rate (PER) and bit error rate (BER), we search for the optimal scaling factor of the transfer function in the output layer of the MLP/BP neural networks and add small random disturbances to the training data. As compared with the conventional MLP/BP-based DFEs and the soft output MLP/BP-based DFEs, the proposed MLP/BP-based soft DFEs under multi-path fading channels can improve over 3-0.6 dB at PER=10-1 and over 3.3-0.8 dB at BER=10-3.

The transport network paradigm is changing as evidenced by IP convergence and the divergence of architectures and technologies. Harnessing the full power of light will spur the creation of new broadband and ubiquitous services networks. To attain this, however, not only must photonic technologies be optimized, but they must also be coordinated with complementary electrical technologies. With regard to photonic network design technologies, further developments are necessary including very large scale network design, quasi-dynamic network design, and multi-layer optical path network design.

During these years, we have been focusing on developing ultra high-data-rate wireless access systems for future wireless multimedia communications. One of such kind of systems is called DPC-OF/TDMA (dynamic parameter controlled orthogonal frequency and time division multiple access) which targets at beyond 100 Mbps data rate. In order to support higher data rates, e.g., several hundreds of Mbps or even Gbps for future wireless multimedia applications (e.g., streaming video and file transfer), it is necessary to enhance DPC-OF/TDMA system based on MIMO-OFDM (multiple-input multiple-output orthogonal frequency division multiplexing) platform. In this paper, we propose an enhanced DPC-OF/TDMA system based on Multi-Layer MIMO-OFDM scheme which combines both diversity and multiplexing in order to exploit potentials of both techniques. The performance investigation shows the proposed scheme has better performance than its counterpart based on full-multiplexing MIMO-OFDM scheme. In addition to the Exhaustive Detection (EXD) scheme which applies the same detection algorithm on each subcarrier independently, we propose the Reduced-Complexity Detection (RCD) scheme. The complexity reduction is achieved by exploiting the suboptimal Layer Detection Order and subcarrier correlation. The simulation results show that huge complexity can be reduced with very small performance loss, by using the proposed detection scheme. For example, 60.7% complexity can be cut off with only 1.1 dB performance loss for the 88 enhanced DPC-OF/TDMA system.

The rapidly increasing bandwidth requirements of IP traffic mean that networks based on optical technologies in conjunction with IP routing technologies will provide the backbone of the next generation Internet. One of the major issues is how to construct an optical-technology-based backbone network that offers the economical transport of large-scale IP/MPLS services while achieving reliable, robust network. The key to achieving this objective lies in multilayer coordination technologies using Multi-Layer Service Network [MLSN] Architecture, that we previously proposed [2]. One of the important aspects of MLSN architecture is ability to effectively use GMPLS network resources by IP/MPLS service networks. We propose extensions to previously proposed MLSN architecture. The proposed extensions to MLSN architecture are tailored to address "service virtualization and separation" of various service networks over GMPLS backbone. As a part of this extended MLSN architecture, we introduce novel concepts known as Logical Router (LR) and Virtual Router (VR) that would enable border router to be services domain router, so that it can connect multiple service networks such as L2VPN, L3VPN etc., over GMPLS backbone by offering service separation or virtualization. This service separation/isolation greatly enhances the reliability of next generation networks, as any failure on one service should be isolated from others. We evaluate our extended network architecture against requirements for the large scale network targeting at introducing such new technology to cope with vast traffic explosion and challenges in operation and service provision sophistication.

We address issues for improving hands-free speech enhancement and speech recognition performance in different car environments using a single distant microphone. This paper describes a new single-channel in-car speech enhancement method that estimates the log spectra of speech at a close-talking microphone based on the nonlinear regression of the log spectra of noisy signal captured by a distant microphone and the estimated noise. The proposed method provides significant overall quality improvements in our subjective evaluation on the regression-enhanced speech, and performed best in most objective measures. Based on our isolated word recognition experiments conducted under 15 real car environments, the proposed adaptive nonlinear regression approach shows an advantage in average relative word error rate (WER) reductions of 50.8% and 13.1%, respectively, compared to original noisy speech and ETSI advanced front-end (ETSI ES 202 050).

This paper proposes a Generalized Traffic Engineering Protocol (GTEP). GTEP is a protocol that permits communication between a Path Computation Element (PCE) and a Generalized Multi-Protocol Label Switching (GMPLS) controller (CNTL). The latter is hosted by each GMPLS node; it handles GMPLS and MPLS protocols such as routing and signaling protocols as well as controlling the GMPLS node host. The PCE provides multi-layer traffic engineering; it calculates Label Switched Path (LSP) routes and judges whether a new lower-layer LSP should be established. GTEP functions are implemented in both the PCE and GMPLS router. We demonstrate a multi-layer traffic engineering experiment conducted with GTEP.

The bandwidth explosion ushered in by the popularity of the Internet has spurred the recent acceleration in the development and deployment of equipment supporting packet based broadband services. This coupled with the widespread deployment of WDM based Optical Transport Systems in the core network to satisfy the corresponding increase in capacity demand, has led network planners for tighter coordination between IP and Optical layers to increase reliability, robustness of next generation backbone network. In this paper, we propose a solution known as border model, which is tailored to address deployment concerns associated with GMPLS technology in existing networks. We extend our proposal to include, "Border model based Multi-layer service network architecture," to provide coordinated multi-layer IP and Optical services, for different network design scenarios. Resource Control is an important aspect of multi-layer service networks. This paper examines next generation requirements for resource control, defines resource control architecture and presents some evaluation results for multi-layer recovery techniques in the context of Multi-layer service network based on border model.