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Recent studies have proposed a model using the supervised neural-network (NN) as the haptic model. However, this model has the problem in expressing human tactile sense. Therefore, we constructed a haptic stage model based on the model of human-tactile sense and cognitive process. Our NN-based model consists of supervised and unsupervised stages. Using surface-scanning results from our trial micro-tactile...
The typical method of entering a password for user authentication is vulnerable to hacking; therefore, various security technologies using bio-signals, such as iris scan, electrocardiography, electromyography (EMG), and fingerprint recognition, are being developed. In this research, an authentication algorithm using an EMG signal is proposed to supplement the weakness of personal certification techniques...
Data diversity in terms of types, styles, as well as radiometric, exposure and texture conditions widely exists in training and test data of vision applications. However, learning in traditional neural networks (NNs) only tries to find a model with fixed parameters that optimize the average behavior over all inputs, without using data-specific properties. In this paper, we develop a meta-level NN...
An application of artificial vision and artificial neural networks techniques in face recognition, is presented. In order to do that, a set of images (frontal face photos) with different lighting conditions, gestures, accessories and distances is used. A stepwise algorithm allows to achieve a satisfactory results, obtaining the correct identification of images inside and outside the data set.
Our previous microphone-array system with a neural network (NN) structure has yielded a sharp directivity by training the NN using temporal-spatial patterns in sound pressure for sinusoidal signals at multiple frequencies. Although this system achieved a sharp directivity for trained and untrained frequencies, the directivity is effective only for sinusoidal signals. In this study, we aim broadbanding...
For a network, knowledge of its Laplacian eigenvalues is central to understand its structure and dynamics. In this paper, we study the Laplacian spectra for a family of treelike networks. Firstly, we calculate the constant term and monomial coefficient of characteristic polynomial. By using the Vieta theorem, we then obtain the sum of reciprocals of all nonzero eigenvalues of Laplacian matrix. We...
This paper considers the pinning synchronization problem for complex networks with directed topologies by utilizing the output state information of network nodes, where the node dynamics satisfies the Lipschitz condition. Based on M-matrix theory and Lyapunov functional method, some sufficient conditions are derived to ensure that the network can be pinned to the trajectory of the leader node. Some...
Neural networks along with expert adaptive regulators and systems with associative memory form the basis of intelligent technologies for information management and processing [1], [2]. This paper introduces an algorithm for the dynamic measurement error correction based on a neural network (NN) inverse model of a measuring transducer (MT). It uses the reduction principle in the compensating filter...
Wireless Sensor Networks (WSNs) are getting popular day by day. But due to the constrained of resources and limited battery supply of sensor nodes, this becomes the major areas of research. Earlier the LEACH protocol proposed contributes a lot in terms of reducing energy consumption among sensor nodes. Later on concept of rendezvous nodes (RZ) and mobile sink was combined with LEACH to reduce energy...
This article explores the problems of automated retail systems, which named are vending machines. The main problem is the formation of an assortment of a vending machine, the realization of which will bring maximum profit. As a modern analysis tool of consumer demand in retail trade artificial intelligence is regarded. Attention is focused on one of the methods of constructing artificial intelligence...
This paper considers architecture and functionality of the embedded data acquisition system for automated beehive monitoring. A description of constructed sensor subsystems is given. Proposed solution acquires hive temperature, humidity and weight referring this data to the mobile application via wireless network. The system also performs an analysis of collected bee noises with artificial neural...
Security of today communication networks depends also on effective hash function. A cryptographic hash function is used to realize a transformation of input to a fixed-size value. This value is called the hash value. One way hash function could be generated also by an artificial neural network (ANN). Theoretical analysis of the possibility of using artificial neural network and chaotic maps for hashing...
This paper proposes an adaptive multiclass neurofuzzy classifier (MC-NFC) for fault detection and classification in solar photovoltaic (PV) systems. The designed fuzzy classifier was optimized by seeking for the best numerical values of the parameters that tune its membership functions. The experiments have been conducted on the basis of collected data from a real time PV array emulator (namely array...
One of many important activities in the Wireless Sensor Network is the localization for tracked devices. Received Signal Strength (RSS) is a parameter of the power level that being received by the radio which can be used to track the location of the devices. This paper evaluates the localization of ZigBee devices which uses RSS fingerprinting by artificial neural networks. The RSS data processing...
Training of Artificial Neural Networks (ANN) is an important step to make the network able to accomplish the desired task. This capacity of learning in such networks makes them applied in many applications as modeling and control. However, many of training algorithms have some drawbacks like: too many parameters to be estimated, important calculus time. In this paper, we propose a very simple method...
Repetitive respiratory disturbance during sleep is called Sleep Apnea Hypopnea Syndrome and causes various diseases. Different features and classifiers have been used by different researchers to detect sleep apnea. This study is undertaken to identify the better performing blood oxygen saturation features subset using an Artificial Neural Network classifier for sleep Apnea detection. A database of...
Security/Safety is managed, mostly, by means of integrated systems which have to consider, more and more, sensors, devices, cameras, mobile terminals, wearable devices, etc. that use wireless networks, to ensure protection of people and/or tangible/intangible assets from voluntary attacks, allowing also the safe management of the related consequent emergency situations that can derive from the above...
In a power distribution network, network topology information is essential for an efficient operation of the network. This information is not accurately available, due to uninformed changes that happen from time to time, or uncertain meter readings. Reliable prediction of system status is a highly demanded functionality of smart energy systems, which can enable users or human operators to react quickly...
This paper proposes a neural network (NN) approach for demodulating output signals of a nonlinear channel with memory. The feed-forward neural network is trained to learn the appropriate mapping between nonlinear input patterns and source bits. The simulation results provide some evidence that neural networks can learn the effect of nonlinear channels with memory and demodulate the output signal of...
Artificial intelligence is widely used in image processing. Neural networks (NN) were successful used for solving complicated issues due to their capacity of generalization and learning from examples. In this paper some aspects of image compression using artificial neural networks are discussed. The network is used in the feedback loop of the visual servoing system, which aims to control a wheeled...
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