The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
A new adaptive load shedding method based on the artificial neural network (ANN) and power flow tracing is proposed in this paper. The ANN is used to estimate the total active power imbalance according to the time interval of frequency drop of the equivalent inertial center from the rated value to the threshold. Load frequency regulation factor and the load priority are incorporated into the power...
In this paper, an impedance control strategy is proposed for a rigid robot collaborating with human by considering impedance learning and human motion intention estimation. The least square method is used in human impedance identification, and the robot can adjust its impedance parameters according to human impedance model for guaranteeing compliant collaboration. Neural networks (NNs) are employed...
This paper proposes a novel hybrid position estimation strategy based on merging two self-sensing techniques according to the operating speed. High-frequency (HF) signal injection algorithm is deployed for zero and low-speeds, while the Machine Learning (ML) method is adopted for medium and high speeds. The proposed position estimator is intended for the fault-tolerant control of an interior permanent-magnet-synchronous...
For automotive applications, accurate torque production capability and high efficiency of the traction motor is very important. However, the performance of widely used interior permanent magnet (IPM) machine is influenced by temperature variation. In this paper, a control algorithm is proposed to compensate the performance variations in IPM machines due to temperature change utilizing current pulse...
In this paper, an Artificial Neural Network (ANN) is employed for the estimation of LaTeral Misalignment (LTM) as well as compensation of its effect on Dynamic Wireless Power Transfer (DWPT) systems for Electric Vehicles (EVs) charging. In a DWPT system, energy efficiency and energy transfer capability are significantly affected by the degree of LTM. Therefore, the real-time estimation of LTM, followed...
Anemia is a condition in which the hemoglobin (Hb) content becomes less than that of the normal value. In this project, hemoglobin value is estimated using ANN (Artificial Neural Network). Database of blood sample images and their actual Hb values is collected from a local laboratory. Red, green and blue normalized values of images' samples are fed to the ANN as input. Cyanemethemoglobin method based...
Fingerprinting based WLAN indoor positioning system (FWIPS) provides a promising indoor positioning solution to meet the growing interests for indoor location-based services (e.g., indoor way finding or geo-fencing). FWIPS is preferred because it requires no additional infrastructure for deploying an FWIPS — achieving the position estimation by reusing the available WLAN and mobile devices, and is...
The linearly constrained minimum variance (LCMV)-beamformer (BF) is a viable solution for desired source extraction from a mixture of speakers in a noisy environment. The performance in terms of speech distortion, interference cancellation and noise reduction depends on the estimation of a set of parameters. This paper presents a new mechanism to update the parameters of the LCMV-BF. A new speech...
A distortionless speech extraction in a reverberant environment can be achieved by an application of a beamforming algorithm, provided that the relative transfer functions (RTFs) of the sources and the covariance matrix of the noise are known. In this contribution, we consider the RTF identification challenge in a multi-source scenario. We propose a successive RTF identification (SRI), based on a...
To understand the behavior of moving entities in a given environment, one should be capable of predicting their motion, that is, to model their dynamics. In a setting where different behaviors can arise, one can assume that each of them corresponds to different motivational states of observed entities. Here, those motivations are understood as goal positions or spots where entities seek to arrive...
Age estimation has recently become increasingly important for a variety of reasons including security, gaming, healthcare, and biometry. In this paper, we are interested in age estimation for content filters which could limit access to age-inappropriate content. Considering that the auditory response to sound varies with age, we provide in this paper preliminary insights about age estimation through...
Software Development Effort Estimation (SDEE) plays a primary role in software project management. Among several techniques suggested for estimating software development effort, analogy-based software effort estimation approaches stand out as promising techniques.In this paper, the performance of Fuzzy Analogy is compared with that of six other SDEE techniques (Linear Regression, Support Vector Regression,...
The robust adaptive control of uncertain system with unknown time-varying control coefficient is discussed. A novel output sampled control scheme based on characteristic model with neural network estimator is proposed. The design of the control scheme includes characteristic modeling, estimation for the characteristic parameters, and characteristic model-based adaptive control. The estimation method...
One of the key technologies to take full advantage of wind power is to establish a wind turbine (WT) generator output estimation system with high accuracy. The static feed forward artificial neural network is widely used in previous WT generator output estimation technology. However, this method has many problems such as local minimization, a lack of dynamics, edge effect, and multi-correlation. To...
In this paper, we propose the use of multiple Gaussian kernels for distributed nonlinear regression or system identification tasks by a network of nodes. By employing multiple kernels in the estimation process we increase the degree of freedom and thus, the ability to reconstruct nonlinear functions. For this, we extend the so-called KDiCE algorithm, which allows a distributed regression of nonlinear...
Within the complex driving environment, progress in autonomous vehicles is supported by advances in sensing and data fusion. Safe and robust autonomous driving can only be guaranteed provided that vehicles and infrastructure are fully aware of the driving scenario. This paper proposes a methodology for feature uncertainty prediction for sensor fusion by generating neural network surrogate models directly...
This paper presents harmonic current estimation using neural network for a power electronic converter. Three types of popular neural architectures namely single hidden layered Feedforward architecture, multi hidden layered Feedforward neural architecture, cascade architecture are considered for investigation. The non-linear load namely diode bridge uncontrolled rectifier with resistive inductive (RL)...
Many noninvasive continuous blood pressure measurements using photoplethysmography (PPG) are still inadequate in terms of accuracy and stability, which hinders the practical application of this method. This paper proposes a model based on ensemble method for BP estimation using PPG. A number of blood pressure calculation base-models is built on the same training data. These base-models are used to...
Various modalities are used for the examination of the gastrointestinal (GI) tract. One such modality is Wireless Capsule Endoscopy (WCE), a non-invasive technique which consists of a swallowable color camera that enables the detection of GI pathology with only minimal patient discomfort. Currently, tracking of the capsule position is estimated in the 3D abdominal space, using radio-frequency (RF)...
A fast, yet accurate nanoscale IC energy estimation is a design-time desideratum for area-delay-power-reliability optimized circuits and architectures. This paper introduces an IC energy estimation approach, which instead of sequentially propagating workload vectors throughout the circuit, relies on an one time propagation of the workload statistics. To this end, the basic gates need be SPICE pre-characterized...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.