Artificial neural networks (ANNs) constitute a class of flexible nonlinear models designed to mimic biological neural systems. In this entry, we introduce ANN using familiar econometric terminology and provide an overview of ANN modeling approach and its implementation methods. † Correspondence: Chung-Ming Kuan, Institute of Economics, Academia Sinica, 128 Academia Road, Sec. 2, Taipei 115, Taiwan; ckuan@econ.sinica.edu.tw. †† I would like to express my sincere gratitude to the editor, Professor Steven Durlauf, for his patience and constructive comments on early drafts of this entry. I also thank Shih-Hsun Hsu and Yu-Lieh Huang for very helpful suggestions. The remaining errors are all mine.

Artificial neural networks

Digital processing of speech signals

Wireless sensor network (WSN) has emerged as one of the most promising technologies for the future. This has been enabled by advances in technology and availability of small, inexpensive, and smart sensors resulting in cost effective and easily deployable WSNs. However, researchers must address a variety of challenges to facilitate the widespread deployment of WSN technology in real-world domains. In this survey, we give an overview of wireless sensor networks and their application domains including the challenges that should be addressed in order to push the technology further. Then we review the recent technologies and testbeds for WSNs. Finally, we identify several open research issues that need to be investigated in future.

Our survey is different from existing surveys in that we focus on recent developments in wireless sensor network technologies. We review the leading research projects, standards and technologies, and platforms. Moreover, we highlight a recent phenomenon in WSN research that is to explore synergy between sensor networks and other technologies and explain how this can help sensor networks achieve their full potential. This paper intends to help new researchers entering the domain of WSNs by providing a comprehensive survey on recent developments.

Wireless sensor networks: a survey on recent developments and potential synergies

Space-air-ground integrated network (SAGIN), as an integration of satellite systems, aerial networks, and terrestrial communications, has been becoming an emerging architecture and attracted intensive research interest during the past years. Besides bringing significant benefits for various practical services and applications, SAGIN is also facing many unprecedented challenges due to its specific characteristics, such as heterogeneity, self-organization, and time-variability. Compared to traditional ground or satellite networks, SAGIN is affected by the limited and unbalanced network resources in all three network segments, so that it is difficult to obtain the best performances for traffic delivery. Therefore, the system integration, protocol optimization, resource management, and allocation in SAGIN is of great significance. To the best of our knowledge, we are the first to present the state-of-the-art of the SAGIN since existing survey papers focused on either only one single network segment in space or air, or the integration of space-ground, neglecting the integration of all the three network segments. In light of this, we present in this paper a comprehensive review of recent research works concerning SAGIN from network design and resource allocation to performance analysis and optimization. After discussing several existing network architectures, we also point out some technology challenges and future directions.

Space-Air-Ground Integrated Network: A Survey

Consider a discrete source producing a sequence of message letters from a finite alphabet. A single-letter distortion measure is given by a non-negative matrix (d ij ). The entryd ij measures the ?cost? or ?distortion? if letteriis reproduced at the receiver as letterj. The average distortion of a communications system (source-coder-noisy channel-decoder) is taken to bed= ? i.j P ij d ij whereP ij is the probability ofibeing reproduced asj. It is shown that there is a functionR(d) that measures the ?equivalent rate? of the source for a given level of distortion. For coding purposes where a leveldof distortion can be tolerated, the source acts like one with information rateR(d). Methods are given for calculatingR(d), and various properties discussed. Finally, generalizations to ergodic sources, to continuous sources, and to distortion measures involving blocks of letters are developed. In this paper a study is made of the problem of coding a discrete source of information, given afidelity criterionor ameasure of the distortionof the final recovered message at the receiving point relative to the actual transmitted message. In a particular case there might be a certain tolerable level of distortion as determined by this measure. It is desired to so encode the information that the maximum possible signaling rate is obtained without exceeding the tolerable distortion level. This work is an expansion and detailed elaboration of ideas presented earlier [1], with particular reference to the discrete case. We shall show that for a wide class of distortion measures and discrete sources of information there exists a functionR(d) (depending on the particular distortion measure and source) which measures, in a sense, the equivalent rateRof the source (in bits per letter produced) whendis the allowed distortion level. Methods will be given for evaluatingR(d) explicitly in certain simple cases and for evaluatingR(d) by a limiting process in more complex cases. The basic results are roughly that it is impossible to signal at a rate faster thanC/R(d) (source letters per second) over a memoryless channel of capacityC(bits per second) with a distortion measure less than or equal tod. On the other hand, by sufficiently long block codes it is possible to approach as closely as desired the rateC/R(d) with distortion leveld. Finally, some particular examples, using error probability per letter of message and other simple distortion measures, are worked out in detail.

Coding Theorems for a Discrete Source With a Fidelity CriterionInstitute of Radio Engineers, International Convention Record, vol. 7, 1959.

The diffusion of Device-to-Device (D2D) communications opens the door to exploit the contributions of multiple Mobile Devices (MDs) to accomplish collaborative tasks In this paper a speaker recognition algorithm for MDs based on a multiple-observations approach is presented We propose various fusion and clustering algorithms aimed at efficiently exploiting data coming from MDs Numerical results show that in many cases our multiple-observation approach is able to significantly improve the accuracy of the considered speaker recognition algorithm

Speaker Recognition Exploiting D2D Communications Paradigm: Performance Evaluation of Multiple Observations Approaches

The diffusion of mobile devices, equipped by many different network interfaces, offers great benefits to mobile communications, in particular in the field of the so called Intelligent Transportation System (ITS). At the same time, the development of the IEEE 802.21 standard, that facilitates the interoperability between different access networks, assures further performance improvements. In this scenario, the network selection, that consists in determining the best Radio Access Network (RAN) among a set of available heterogeneous links, plays a fundamental role. The main contribution of this paper is a performance comparison among different network selection algorithms, within the framework proposed by the 802.21 standard. This performance comparison is obtained through a simulator developed by using Network Simulator 2 (ns-2).

http://ieeexplore.ieee.org/iel7/6588700/6595732/06595759.pdf

Simulative performance comparison of network selection algorithms in the framework of the 802.21 standard

The reference environment is composed of a sensor network that conveys information towards earth stations (called sinks) that give access to the satellite backbone and, through it, to the destination. The choice of the sink where to convey sensor information may affect the overall communication performance. After introducing the application environment, the paper introduces a method to select the sink that assures the improvement of network performance in terms of energy consumption, load, and total time spent by information packets in the network, considering the fading level measured by earth stations. After selecting the sink, the technique how to propagate information within the sensor network has a main role. The paper compares flooding-based techniques on the basis of the metrics mentioned above.

Information Distribution Techniques in Sensor Networks via Satellite

Recent multimedia and location-based services (LBSs) employ information about location, orientation and context of a mobile device. Moreover, the wide spread adoption of Smartphones, usually equipped with powerful processors, accelerometers, compasses and Global and Hybrid Positioning Systems (GPS/HPSs) receivers, has favored the increasing of location- and context-based services over the last years. In this work a novel Location Recognition approach aimed at supporting location aware services, in particular Check-In services, is presented. The proposed method uses both the GPS/HPS positioning information and, in an opportunistic way, the presence of Wi-Fi Access Points (APs). The method is based on the concept of radio FingerPrint (FP) whose definition proposed in this paper, to the best of authors' knowledge, has never been applied previously. The method is suited to be employed where traditional approaches — usually based only on GPS/HPS − fail, as in case of indoor or dense urban environments. Finally, the proposal, practically realized over different Android OS Smartphones, has been tested in terms of performance. The experimental results are very satisfying and open the doors to a wide employment of the method.

Smartphone-based automatic place recognition with Wi-Fi signals for location-aware services

This paper tackles the classical problem of transmission rate allocation in satellite networks where fading may negatively impact communications. Within the framework of multiobjective programming (MOP), this paper introduces a transmission rate allocation criterion among Earth stations (ESs) called $L_p$ -problem-based rate allocation $(L_{p}RA)$ . The allocations provided by $L_{p}RA$ are representative of a compromise among the need of different performance metrics such as packet loss and transmission power (TP). This paper determines the condition for the existence and the value of a $L_{p}RA$ transmission rate allocation bound $R^{\mathrm{bound}}$ , to which the transmission rate globally allocated by $L_{p}RA$ converges when the overall available transmission rate $R_{\mathrm{TOT}}$ tends to infinity. The performance analysis, which is carried out through simulations under different satellite channel conditions, is aimed at investigating $L_{p}RA$ features, at showing the existence of the rate bound and the advantages concerning the rate allocation given by using $L_{p}RA$ , and at comparing $L_{p}RA$ with two other schemes in the literature concerning allocated rate, packet loss rate, transmit power, and execution time.

Igor Bisio

Papers

Speaker Recognition Exploiting D2D Communications Paradigm: Performance Evaluation of Multiple Observations Approaches

Simulative performance comparison of network selection algorithms in the framework of the 802.21 standard

Information Distribution Techniques in Sensor Networks via Satellite

Smartphone-based automatic place recognition with Wi-Fi signals for location-aware services

$L_p$ -Problem-Based Transmission Rate Allocation With Packet Loss and Power Metrics Over Satellite Networks