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.
Shannon observed that the normal distribution has maximal entropy among distributions with a density function and a given variance. This sparked a significant body of research in statistics, broadly concerned with goodness-of-fit estimators based on Shannon entropy for a variety of distributions and, in particular, normality testing. The present paper proposes to use compression algorithms and other...
In this paper, a novel iterative equalizer applying soft feedback is introduced, the 2 symbols ISDIC (2S ISDIC) equalizer. The 2S ISDIC is the first equalizer that bridges the gap between the low complexity ISDIC equalizer which has poor performance, to the high complexity inverse channel equalizing methods, such as the LMMSE and the MMSE ISDIC equalizers, which have better performances. The 2S ISDIC...
The delivery of educational activities that are tailored and adapted to the student knowledge level is a fundamental aspect of educational systems. In order to provide exercises and learning activities of appropriate difficulty, their level of difficulty should be accurately determined. In this paper, we present a neuro-fuzzy approach that determines the difficulty level of exercises on search algorithms...
The Kernel Mean Matching (KMM) is an elegant algorithm that produces density ratios between training and test data by minimizing their maximum mean discrepancy in a kernel space. The applicability of KMM to large-scale problems is however hindered by the quadratic complexity of calculating and storing the kernel matrices over training and test data. To address this problem, this paper proposes a novel...
Software features and costs are often unquantifiable due to the abstract nature of software. In many cases, this results in the estimated costs of software development projects to be potentially highly biased, highly inaccurate, or highly unjustified. Hence, current software estimation methodologies can open up areas for corruption as estimated budgets and costs are difficult to verify and validate...
In this paper novel project scheduling difficulty estimations are proposed for Multi-Skill Resource-Constrained Project Scheduling Problem (MS-RCPSP). The main goal of introducing the complexity estimations is an attempt of estimation the project complexity before launching the optimization process. What is more, the dataset instance generator is also presented as a tool to create new instances for...
In this paper, a novel iterative equalizer is introduced, the two symbols ISDIC (2S ISDIC) equalizer. The 2S ISDIC is the first equalizer that bridges the gap between the low complexity ISDIC equalizer which has poor performance, to the high complexity inverse channel equalizing methods, such as the LMMSE and the MMSE ISDIC equalizers, which have better performances. The 2S ISDIC will be incorporated...
This paper addresses the issue of UWB signal acquisition in the context of wireless powered UWB RFID systems. In this scenario, the data transmission is based on short packet so as to meet the micro-power budget of autonomous power harvesting. The burst short packet transmission as well as the low duty cycling UWB pulse modulation places a stringent challenge at the UWB receiver for timing acquisition...
In this paper we propose a novel method for depth estimation based on a single recording of a focused plenoptic camera. The presented algorithm is based on multiple stereo-observations within the multi-view micro images of the focused plenoptic camera. Here, pixel correspondences are found based on local intensity error minimization. Since our algorithm works directly on the micro images, no sub-aperture...
This paper investigates low complexity detection for multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems with co-channel interference (CCI). We firstly derive minimum mean square error (MMSE) detection based on sorted QR decomposition (SQRD) and modified MMSE SQRD detection for MIMO-OFDM systems with CCI. Although better performance can be achieved by the...
Considering both inefficiency of the pilot usage and high complexity of current carrier synchronization algorithms for burst-mode systems, a novel distributed joint time-frequency domain (DJTFD) carrier synchronization algorithm is proposed. The frequency-domain estimation has a large residual offset with limited pilot overhead. So we need the distributed time-domain estimation to guarantee both large...
The performance of coded MIMO systems can be enhanced by effectively utilizing soft iterative estimation techniques at the receiver. The main concern on this iterative techniques is computational complexity and feasibility of the hardware implementation. This paper evaluates a number of soft iterative MIMO detection schemes in terms of the bit error rate performance as well as computational complexity...
A new type of recursive soft sequential estimation (RSSE) algorithm is presented. The algorithm can be used for fast initial synchronization of pseudonoise (PN) signals based on m-sequences. The key feature of the algorithm is the grouping of binary symbols and the reception of the group as a whole symbol. Different numbers of binary symbols in the group lead to different estimation algorithms in...
Class discovery, which aims to identify the underlying category structure, is an important issue in pattern recognition and knowledge discovery. The key task in class discovery is to estimate the number of classes. Classical estimation approaches usually face the problems of low accuracy, high complexity, or difficulty in choosing an appropriate penalty function. In this paper, an effective class...
Analog front-ends for wide-band wireless communication systems exhibit frequency-selective inphase and quadrature (I/Q) imbalance due to asymmetry in devices and layouts. This imbalance leads to a significant degradation of the performance in orthogonal frequency division multiplexing (OFDM) systems. In this paper, using a loop-back method, a joint transmitter (TX) and receiver (RX) estimation and...
Either any of the current global or non-local stereo matching algorithms cannot be good enough to show both matching accuracy and calculation efficiency during the matching processing, especially while there are less texture regions or the images are captured from real scene. Therefore, the goal of our research is to break current bottleneck of stereo matching in aspects of the precision and speed,...
Reconstruction problem for signals generated by discrete nonlinear dynamic system is considered via unified approach to recurrent kernel-based dynamic systems. In order to prevent the model complexity increasing under on-line identification, the reduced order model kernel method is proposed and proper recurrent Least-Square identification algorithms are designed along with conventional regularization...
We experimentally demonstrate an effective multiplier-free blind phase noise estimation technique for CO-OFDM systems for the first time based on the statistical properties of the received symbols' phases. Our technique operates in polar coordinates, providing very low implementation c omplexity.
Changing the development environment can have severe impacts on the system behavior such as the execution-time performance. Since it can be costly to migrate a software application, engineers would like to predict the performance parameters of the application under the new environment with as little effort as possible. In this paper, we concentrate on model-driven development and provide a methodology...
Based on the Multitask Bayesian Compressive Sensing (MT-BCS) framework, a novel DOA estimation approach for planar array is proposed in this paper. Different from the traditional CS-based DOA model, where the spatial observation is characterized in one large scale matrix, to reduce the complexity, a separable observation structure is proposed, which separates the joint spatial observation into two...
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.