100,285 research outputs found
Performance of the wavelet-transform-neural network based receiver for DPIM in diffuse indoor optical wireless links in presence of artificial light interference
Artificial neural network (ANN) has application in communication engineering in diverse areas such as channel equalization, channel modeling, error control code because of its capability of nonlinear processing, adaptability, and parallel processing. On the other hand, wavelet transform (WT) with both the time and the frequency resolution provides the exact representation of signal in both domains. Applying these signal processing tools for channel compensation and noise reduction can provide an enhanced performance compared to the traditional tools. In this paper, the slot error rate (SER) performance of digital pulse interval modulation (DPIM) in diffuse indoor optical wireless (OW) links subjected to the artificial light interference (ALI) is reported with new receiver structure based on the discrete WT (DWT) and ANN. Simulation results show that the DWT-ANN based receiver is very effective in reducing the effect of multipath induced inter-symbol interference (ISI) and ALI
Modeling Maintenance Productivity Measurement of Engineering Production Systems: Discrete Event Simulation Approach
Modeling and simulation of industrial information communication systems and networks is one of the
major concerns of productivity engineers for the establishment of productivity standards in virtually
all functional areas of an industrial organization. Maintenance function is one of such areas that have
always engaged the attention of engineering productivity practitioners. However, one of the basic prob-
lems is the difficulty in setting up integrated but easy and practical measurement schemes. Even where
the measures are set up, the approaches to measurement sometimes are conflicting. Therefore the need
for an integrated approach to optimize the basket of parameters measured remains.
In this chapter the author attempts to identify approaches in integrated and systematic maintenance
productivity measurement and create models for optimising total productivity in maintenance systems.
Visual yardstick, utility, queuing systems and simulations approaches for measurement of maintenance
productivity are all discussed with a particular focus on markov chain approach for stochastic break-
downs in repairable systems.. The chapter also shows how understanding the impact of plant failure and
repair/service distributions assists in providing measures for maintenance productivity using discrete
event system simulation
Guest Editorial: Nonlinear Optimization of Communication Systems
Linear programming and other classical optimization techniques have found important applications in communication systems for many decades. Recently, there has been a surge in research activities that utilize the latest developments in nonlinear optimization to tackle a much wider scope of work in the analysis and design of communication systems. These activities involve every “layer” of the protocol stack and the principles of layered network architecture itself, and have made intellectual and practical impacts significantly beyond the established frameworks of optimization of communication systems in the early 1990s. These recent results are driven by new demands in the areas of communications and networking, as well as new tools emerging from optimization theory. Such tools include the powerful theories and highly efficient computational algorithms for nonlinear convex optimization, together with global solution methods and relaxation techniques for nonconvex optimization
Performance evaluation of two-fuzzy based cluster head selection systems for wireless sensor networks
Sensor networks supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities are emerging as a critically important computer class that enable novel and low cost applications. There are many fundamental problems that sensor networks research will have to address in order to ensure
a reasonable degree of cost and system quality. Cluster formation and cluster head selection are important problems in sensor
network applications and can drastically affect the network’s communication energy dissipation. However, selecting of the
cluster head is not easy in different environments which may have different characteristics. In this paper, in order to deal with this problem, we propose two fuzzy-based systems for cluster head selection in sensor networks. We call these systems: FCHS
System1 and FCHS System2. We evaluate the proposed systems by simulations and have shown that FCHS System2 make a good selection of the cluster head compared with FCHS System1 and another previous system.Peer ReviewedPostprint (published version
IEEE Access special section editorial: Artificial intelligence enabled networking
With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS)
An Efficient Transport Protocol for delivery of Multimedia An Efficient Transport Protocol for delivery of Multimedia Content in Wireless Grids
A grid computing system is designed for solving complicated scientific and
commercial problems effectively,whereas mobile computing is a traditional
distributed system having computing capability with mobility and adopting
wireless communications. Media and Entertainment fields can take advantage from
both paradigms by applying its usage in gaming applications and multimedia data
management. Multimedia data has to be stored and retrieved in an efficient and
effective manner to put it in use. In this paper, we proposed an application
layer protocol for delivery of multimedia data in wireless girds i.e.
multimedia grid protocol (MMGP). To make streaming efficient a new video
compression algorithm called dWave is designed and embedded in the proposed
protocol. This protocol will provide faster, reliable access and render an
imperceptible QoS in delivering multimedia in wireless grid environment and
tackles the challenging issues such as i) intermittent connectivity, ii) device
heterogeneity, iii) weak security and iv) device mobility.Comment: 20 pages, 15 figures, Peer Reviewed Journa
DCCII-Based Novel Lossless Grounded Inductance Simulators With No Element Matching Constrains
In 1996, the differential current conveyor (DCCII) was introduced as a versatile active element with current differencing capability. Therefore, in this study, the usefulness of the DCCII is shown on six novel lossless grounded inductance simulator circuits. Proposed circuits simultaneously employ minimum number of elements, i.e. single DCCII, one capacitor, and two resistors. No passive element matching restriction is needed and all solutions are electronically tunable in case that one of resistors is replaced by MOSFET-based voltage-controlled resistor. The internal structure of the active element has been implemented using the TSMC 0.25 um SCN025 CMOS process BSIM3v3.1 parameters. Firstly, the performance of the selected inductor simulator is evaluated and subsequently verified in the design of 5th-order high-pass ladder and 2nd-order frequency filters. In addition, experimental results using commercially available AD844/ADs are given to verify the theoretical analysis and SPICE simulations
Chaos-based communication scheme using proportional and proportional-integral observers
In this paper, we propose a new chaos-based communication scheme using the observers. The novelty lies in the masking procedure that is employed to hide the confidential information using the chaotic oscillator. We use a combination of the addition and inclusion methods to mask the information. The performance of two observers, the proportional observer (P-observer) and the proportional integral observer (PI-observer) is compared that are employed as receivers for the proposed communication scheme. We show that the P-observer is not suitable scheme since it imposes unpractical constraints on the messages to be transmitted. On the other hand, we show that the PI-observer is the better solution because it allows greater flexibility in choosing the gains of the observer and does not impose any unpractical restrictions on the message
Wavelet transform - artificial neural network receiver with adaptive equalisation for a diffuse indoor optical wireless OOK link
This paper presents an alternative approach for signal detection and equalization using the continuous wavelet transform (CWT) and the artificial neural network (ANN) in diffuse indoor optical wireless links (OWL). The wavelet analysis is used for signal preprocessing (feature extraction) and the ANN for signal detection. Traditional receiver architectures based on matched filter (MF) experience significant performance degradation in the presence of artificial light interference (ALI) and multipath induced intersymbol interference (ISI). The proposed receiver structure reduces the effect of ALI and ISI by selecting a particular scale of CWT that corresponds to the desired signal and classifying the signal into binary 1 and 0 based on an observation vector. By selecting particular scales corresponding to the signal, the effect of ALI is reduced. We show that there is little variation when using 30 and 5 neurons in the first layer, with one layer ANN model showing a consistently worse BER performance than other models, whilst the 15 neuron model show some behaviour anomalies from a BER of approximately 10-3. The simulation results show that the Wavelet-ANN architecture outperforms the traditional MF based receiver even with the filter is matched to the ISI affected pulse shape. The Wavelet-ANN receiver is also capable of providing a bit error rate (BER) performance comparable to the equalized forms of traditional receiver structure
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