Least Squares Identification for Hammerstein Multi-input Multi-output Systems Based on the Key-Term Separation Technique

System modeling and parameter estimation are basic for system analysis and controller design. This paper considers the parameter identification problem of a Hammerstein multi-input multi-output (H-MIMO) system. In order to avoid the product terms in the identification model, we derive a pseudo-linear identification model of the H-MIMO system through separating a key term from the output equation of the system and present a hierarchical generalized least squares (LS) algorithm for estimating the parameters of the system. Moreover, we present a new LS algorithm to reduce the computational burden. The proposed algorithms are simple in principle and can achieve a higher computational efficiency than the over-parameterization-based LS estimation algorithm. Finally, we test the proposed algorithms by the simulation example and show their effectiveness.     

Least Squares-Based Iterative Identification Methods for Linear-in-Parameters Systems Using the Decomposition Technique

By extending the least squares-based iterative (LSI) method, this paper presents a decomposition-based LSI (D-LSI) algorithm for identifying linear-in-parameters systems and an interval-varying D-LSI algorithm for handling the identification problems of missing-data systems. The basic idea is to apply the hierarchical identification principle to decompose the original system into two fictitious sub-systems and then to derive new iterative algorithms to estimate the parameters of each sub-system. Compared with the LSI algorithm and the interval-varying LSI algorithm, the decomposition-based iterative algorithms have less computational load. The numerical simulation results demonstrate that the proposed algorithms work quite well.     

A Multi-innovation Recursive Least Squares Algorithm with a Forgetting Factor for Hammerstein CAR Systems with Backlash

This study addresses the identification of Hammerstein CAR systems with backlash, where the nonlinear backlash is described as one regression identification model using a two switching function mathematical model. In such a case, the Hammerstein CAR systems with backlash can be transformed into a piecewise linearized model. Then, a novel multi-innovation recursive least squares algorithm with a forgetting factor is applied to estimate the parameters of the proposed model. Finally, numerical examples are presented to test the performance of the proposed algorithm.     

An Optimally Fair Coin Toss

We address one of the foundational problems in cryptography: the bias of coin-flipping protocols. Coin-flipping protocols allow mutually distrustful parties to generate a common unbiased random bit, guaranteeing that even if one of the parties is malicious, it cannot significantly bias the output of the honest party. A classical result by Cleve (Proceedings of the 18th annual ACM symposium on theory of computing, pp 364–369, 1986) showed that for any two-party \(r\)-round coin-flipping protocol there exists an efficient adversary that can bias the output of the honest party by \(\varOmega (1/r)\). However, the best previously known protocol only guarantees \(O(1/\sqrt{r})\) bias, and the question of whether Cleve’s bound is tight has remained open for more than 20 years. In this paper, we establish the optimal trade-off between the round complexity and the bias of two-party coin-flipping protocols. Under standard assumptions (the existence of oblivious transfer), we show that Cleve’s lower bound is tight: We construct an \(r\)-round protocol with bias \(O(1/r)\).     

Switchless compact dual-band matching networks for class-E power amplifiers

Two compact switchless dual-band load networks for class-E power amplifier (PA) operating at 800 and 1900 MHz are proposed, featuring small area and low loss which will be suitable for non-concurrent dual-band PA module in handset. Theoretical analysis and design equations are provided along with a loss model, including loss in the transistor and in the load network. Loss model is extracted for each structure to find the design parameters for optimized and balanced efficiency in both bands. Both designs are fabricated on Rogers RO4003 substrate with lumped components. Full PA simulations of both bands are carried out with co-simulation using a Triquint TGF2023-2-10 GaN transistor model, lumped components and EM models of load network layouts for both structures. The PA with transformer-based load network achieves a power added efficiency of 68.6 % at low band and 62.6 % at high band at an output power of 37.8 and 36.7 dBm respectively. The overall area consumed by the load network is 13.5 × 9.6 mm². The LC-based PA has a similar PAE of 68.3 and 60 % at low band and high band, respectively. The output power is 38.1 dBm in the low band and 37 dBm in the high-band. The overall area consumed by the load network is 9 × 10 mm²     

A 10-Transistor 65 nm SRAM Cell Tolerant to Single-Event Upsets

A novel SRAM cell tolerant to single-event upsets (SEUs) is presented in this paper. By adding four more transistors inside, the proposed circuit can obtain higher critical charge at each internal node compared to the conventional 6-transistor (6T) cell. Arrays of 2k-bit capacitance of these two designs were implemented in a 65 nm CMOS bulk technology for comparison purpose. Radiation experiments showed that, at the nominal 1.0 V supply voltage, the proposed cell achieves 47.1 % and 49.3 % reduction in alpha and proton soft error rates (SER) with an area overhead of 37 %.     

Exploring Social Networks and Improving Hypertext Results for Cloud Solutions

Internet technologies are constantly evolving as well as the way people use them. Search engines help users to find higher and better relevant results to their searches. Cloud Computing is an evolution of the Internet services and provides a step further ecosystem that can be used to improve the search of more relevant results. Each search engine is based on different modules in order to retrieve the results expected by users using specific keywords. Social networks appear as a reliable Web technology that can directly support a content search. Several studies have been performed showing the growth of social networks in people lives. Using the cloud computing paradigm it is possible to propose a more scalable and efficient way to explore public information available on online social networks. This paper includes the analyses of several social networks services, available contents, cloud-crawlers, and information extraction. In order to collect relevant data from social networks, a social crawler on cloud is proposed. The new approach provides a cloud-based crawler for low-cost, effective, and personalized search models. Moreover, a new algorithm to rank Web documents is proposed and demonstrated. The proposed system is evaluated in comparison with the top Internet search engine, Google, its behavior is very promising, and it is ready for use.     

GreenBikeNet: an Intelligent Mobile Application with Green Wireless Networking for Cycling in Smart Cities

In this paper, we introduce a mobile application with intelligent systems to provide services for cyclists and enhance their cycling experiences in smart cities. The application utilizes smartphones and low-power ZigBee technology for ad-hoc networking. Since ZigBee chipsets have not been included yet in recent smartphones, we develop a Smartphone-ZigBee embedded system that we use in building a mobile application for low-power low-bandwidth wireless ad-hoc networking with acceptable ranges. Cyclists can join either public networks or create their own private networks to exchange information and utilize several developed services. For voice communication between cyclists, we develop a multilingual voice communication system with an innovative smart spectrum and energy management approach. A sender cyclist can speak in his own language while being translated and heard in a clear voice by the receiver cyclist in another language with an acceptable delay less than 1 s. We also develop an intelligent geo-localization system that utilizes smartphone’s GPS receiver to provide real-time geo-locations and speeds of all cyclists connected to the same network on a visual interactive map. The latter system adaptively manages the number of visits to the GPS receiver according to various system parameters to reduce power consumption. Moreover, we develop an emergency system that provides a platform for efficient collaboration between cyclists in emergency conditions. To ensure safety of cyclists, all our services are accessed vocally. Furthermore, we provide an energy harvesting system using the movement of the bike for power generation.     

Intelligent Sensing for Citizen Science

Interest in Citizen Science has grown significantly over the last decade. Much of this interest can be traced to the provision of sophisticated platforms that enable seamless collaboration, cooperation and coordination between professional and amateur scientists. In terms of field research, smart-phones have been widely adopted, automating data collection and enriching observations with photographs, sound recordings and GPS coordinates using embedded sensors hosted on the device itself. Interaction with external sensor platforms such as those normally used in the environmental monitoring domain is practically null-existent. Remedying this deficiency would have positive ramifications for both the professional and citizen science communities. To illustrate the relevant issues, this paper considers a common problem, that of data collection in sparse sensor networks, and proposes a practical solution that would enable citizen scientists act as Human Relays thus facilitating the collection of data from such networks. Broader issues necessary for enabling intelligent sensing using common smart-phones and embedded sensing technologies are then discussed.