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2017 Journal article Open Access OPEN

Persistent homology to analyse 3D faces and assess body weight gain
Giorgi D., Pascali M. A., Henriquez P., Matuszewski B. J., Colantonio S., Salvetti O.
In this paper, we analyse patterns in face shape variation due to weight gain. We propose the use of persistent homology descriptors to get geometric and topological information about the configuration of anthropometric 3D face landmarks. In this way, evaluating face changes boils down to comparing the descriptors computed on 3D face scans taken at different times. By applying dimensionality reduction techniques to the dissimilarity matrix of descriptors, we get a space in which each face is a point and face shape variations are encoded as trajectories in that space. Our results show that persistent homology is able to identify features which are well related to overweight and may help assessing individual weight trends. The research was carried out in the context of the European project SEMEOTICONS, which developed a multisensory platform which detects and monitors over time facial signs of cardio-metabolic risk.Source: The visual computer 33 (2017): 549–563. doi:10.1007/s00371-016-1344-7
DOI: 10.1007/s00371-016-1344-7
Project(s): SEMEOTICONS via OpenAIRE

See at: Central Lancashire Online Knowledge Open Access | ISTI Repository Open Access | The Visual Computer Restricted | The Visual Computer Restricted | The Visual Computer Restricted | link.springer.com Restricted | The Visual Computer Restricted | The Visual Computer Restricted | The Visual Computer Restricted | CNR ExploRA Restricted


2017 Journal article Open Access OPEN

Variance analysis of unbiased complex-valued lp-norm minimizer
Chen Y., So H. C., Kuruoglu E. E., Yang X. L.
Parameter estimation from noisy complex-valued measurements is a significant topic in various areas of science and engineering. In this aspect, an important goal is finding an unbiased estimator with minimum variance. Therefore, variance analysis of an estimator is desirable and of practical interest. In this paper, we concentrate on analyzing the complex-valued â,,"p-norm minimizer with pâ?¥1. Variance formulas for the resultant nonlinear estimators in the presence of three representative bivariate noise distributions, namely, α-stable, Student's t and mixture of generalized Gaussian models, are derived. To guarantee attaining the minimum variance for each noise process, optimum selection of p is studied, in the case of known noise statistics, such as probability density function and corresponding density parameters. All our results are confirmed by simulations and are compared with the Cramér-Rao lower bound.Source: Signal processing (Print) 135 (2017): 17–25. doi:10.1016/j.sigpro.2016.12.018
DOI: 10.1016/j.sigpro.2016.12.018

See at: ISTI Repository Open Access | Signal Processing Restricted | Signal Processing Restricted | Signal Processing Restricted | Signal Processing Restricted | CNR ExploRA Restricted | Signal Processing Restricted | Signal Processing Restricted


2017 Journal article Open Access OPEN

Processing satellite imagery to detect and identify non-collaborative vessels
Reggiannini M., Righi M.
In recent years, European maritime countries have had to deal with new situations involving the traffic of illegal vessels. In order to tackle such problems, systems are required that can detect relevant anomalies such as unauthorised fishing or irregular migration and related smuggling activity. The OSIRIS project aims to contribute to a solution to these problems with the use of large scale data provided by satellite missions (Sentinel, Cosmo-SkyMed, EROS). Optical/SAR data and system Integration for Rush Identification of Ship models (OSIRIS) is a European Space Agency project launched in March 2016, with the primary purpose of developing a software platform dedicated to maritime surveillance. The platform will be in charge of: (i) collecting maritime remote sensing data provided by satellite missions such as Sentinel-1, Sentinel-2, Cosmo-SkyMed and EROS-B, and (ii) processing the acquired data in order to detect and classify seagoing vessels. A main goal within OSIRIS is to develop computational imaging procedures to process Synthetic Aperture Radar and Optical data returned by satellite sensors. We propose a system to automatically detect and recognise all the vessels within in a given area; the maritime satellite imagery will be processed to extract visual informative features of candidate vessels and to assign an identification label to each vessel.Source: ERCIM news (2017): 25–26.

See at: ercim-news.ercim.eu Open Access | ISTI Repository Open Access | CNR ExploRA Open Access


2017 Contribution to book Open Access OPEN

A low cost, portable device for breath analysis and self-monitoring, the Wize sniffer
Germanese D., Righi M., Benassi A., D'Acunto M., Leone R., Magrini M., Paradisi P., Puppi D., Salvetti O.
Here we describe the implementation of the first prototype of the Wize Sniffer 1.x (WS 1.x), a low cost, portable electronic device for breath analysis. The device is being developed in the framework of the Collaborative European Project SEMEOTICONS (SEMEiotic Oriented Technology for Individuals CardiOmetabolic risk self-assessmeNt and Self-monitoring). In the frame of SEMEOTICONS project, the Wize Sniffer will help the user monitor his/her state of health, in particular giving feedbacks about those noxious habits for cardio-metabolic risk, such as alcohol intake and smoking. The low cost and compactness of the device allows for a daily screening that, even if without a real diagnostic meaning, could represent a pre-monitoring, useful for an optimal selection of more sophisticated and standard medical analysis.Source: Applications in Electronics Pervading Industry, Environment and Society, edited by Alessandro De Gloria, pp. 51–57. CH-6330 Cham (ZG): Springer International Publishing, 2017
DOI: 10.1007/978-3-319-47913-2_7
Project(s): SEMEOTICONS via OpenAIRE

See at: ISTI Repository Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | Archivio della Ricerca - Università di Pisa Restricted | link.springer.com Restricted | link.springer.com Restricted | link.springer.com Restricted | CNR ExploRA Restricted | rd.springer.com Restricted


2017 Journal article Open Access OPEN

The information capacity of the genetic code: is the natural code optimal?
Kuruoglu E. E, Arndt P. F.
We envision the molecular evolution process as an information transfer process and provide a quantitative measure for information preservation in terms of the channel capacity according to the channel coding theorem of Shannon. We calculate Information capacities of DNA on the nucleotide (for non-coding DNA) and amino acid (for coding DNA) level using various substitution models. We extend our results on coding DNA to a discussion about the optimality of the natural codon-amino acid code. We provide the results of an adaptive search algorithm in the code domain and demonstrate the existence of a large number of genetic codes with higher information capacity. Our results support the hypothesis of an ancient extension from a 2-nucleotide codon to the current 3-nucleotide codon code to encode the various amino acids.Source: Journal of theoretical biology 419 (2017): 227–237. doi:10.1016/j.jtbi.2017.01.046
DOI: 10.1016/j.jtbi.2017.01.046

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2017 Contribution to journal Open Access OPEN

Advanced infrared technology and applications 2015
Moroni D., Raimondi V, Sakagami T.
Source: Measurement science & technology (Print) 28 (2017). doi:10.1088/1361-6501/aa59be
DOI: 10.1088/1361-6501/aa59be

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2017 Journal article Open Access OPEN

Seafloor analysis and understanding for underwater archeology
Reggiannini M., Salvetti O.
Surveying the oceans' floors represents at the same time a demanding and relevant task to operators concerned with marine biology, engineering or sunken cultural heritage preservation. Scientific researchers and concerned persons combine their effort to pursue optimized solutions aiming at the mapping of underwater areas, the detection of interesting objects and, in case of archeological survey mission, the safeguard of the detected sites. Among the typical tools exploited to perform the cited operations the Autonomous Underwater Vehicles (AUVs) represent a validated and reliable technology. These vehicles are typically equipped with properly selected sensors that collect data from the surveyed environment. This data can be employed to detect and recognize targets of interest, such as manmade artifacts located on the seabed, both in an online or offline modality. The adopted approach consists in laying emphasis on the amount of regularity contained in the data, referring to the content of geometrical shapes or textural surface patterns. These features can be used to label the environment in terms of more or less interesting areas, where more interesting refers to higher chances of detecting the sought objects (such as man-made objects) in the surveyed area. This paper describes the methods developed to fulfill the purposes of mapping and object detection in the underwater scenario and presents some of the experimental results obtained by the implementation of the discussed techniques in the underwater archeology field.Source: Journal of cultural heritage 24 (2017): 147–156. doi:10.1016/j.culher.2016.10.012
DOI: 10.1016/j.culher.2016.10.012

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2017 Report Closed Access

SEMEOTICONS - Model final tuning
Colantonio S., Coppini G., Zuccalà C. V.
In this document, we outline the advisable actions to be taken into account for further development of the Wize Mirror. In particular, it emerged that some technological improvement of data acquisition procedures might be useful to enhance the Wize Mirror usage in a general setting such as at home. As far as the semantic integration performed by the Virtual Individual Model (VIM), no specific adjustment seems advisable at present. In fact, the VIM and the Wellness Index (WI) were able to describe the user status coherently with clinical and psychological characterisation of the volunteers enrolled in validation campaign.Source: Project report, SEMEOTICONS, Deliverable D6.4, 2017
Project(s): SEMEOTICONS via OpenAIRE

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2017 Journal article Open Access OPEN

Lip segmentation based on Lambertian shadings and morphological operators for hyper-spectral images
Danielis A., Giorgi D., Larsson M., Stromberg T., Colantonio S., Salvetti O.
Lip segmentation is a non-trivial task because the colour difference between the lip and the skin regions maybe not so noticeable sometimes. We propose an automatic lip segmentation technique for hyper-spectral images from an imaging prototype with medical applications. Contrarily to many other existing lip segmentation methods, we do not use colour space transformations to localise the lip area. As input image, we use for the first time a parametric blood concentration map computed by using narrow spectral bands. Our method mainly consists of three phases: (i) for each subject generate a subset of face images enhanced by different simulated Lambertian illuminations, then (ii) perform lip segmentation on each enhanced image by using constrained morphological operations, and finally (iii) extract features from Fourier-based modeled lip boundaries for selecting the lip candidate. Experiments for testing our approach are performed under controlled conditions on volunteers and on a public hyper-spectral dataset. Results show the effectiveness of the algorithm against low spectral range, moustache, and noise.Source: Pattern recognition 63 (2017): 355–370. doi:10.1016/j.patcog.2016.10.007
DOI: 10.1016/j.patcog.2016.10.007
Project(s): SEMEOTICONS via OpenAIRE

See at: ISTI Repository Open Access | Pattern Recognition Restricted | Pattern Recognition Restricted | Pattern Recognition Restricted | Pattern Recognition Restricted | CNR ExploRA Restricted | Pattern Recognition Restricted | Pattern Recognition Restricted


2017 Journal article Open Access OPEN

The SENSEable Pisa project: citizen-participation in monitoring acoustic climate of Mediterranean city centres
Vinci B., Tonacci A., Caudai C., De Rosa P., Nencini L., Pratali L.
The concept of urban sustainability and liveability closely depends on multi-level approaches to environmental issues. The ultimate goal in the field of noise management is to involve citizens and facilitate their participation in urban environmental decisions. The SENSEable Pisa project, based on the concept of Real-Time City and Smart City, presents an acoustic urban monitoring system based on a low-cost data acquisition method for a pervasive outdoor noise measurement. The system is based on the use of noise sensors located on private houses in the centre of Pisa, which provide a good model for the current acoustic climate of Mediterranean city centres. In this study, SENSEable acquisitions show a strong anthropogenic component not revealed by public strategic maps. The anthropogenic component, commonly known as movida, becomes increasingly critical in Mediterranean cities, therefore, it is necessary to explore methods highlighting this new source and to adopt strategies for the creation of reliable noise pollution maps.Source: Clean (Weinh., Internet) 45 (2017). doi:10.1002/clen.201600137
DOI: 10.1002/clen.201600137

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2017 Report Open Access OPEN

ISTI Young Research Award 2017
Barsocchi P., Basile D., Candela L., Ciancia V., Delle Piane M., Esuli A., Ferrari A., Girardi M., Guidotti R., Lonetti F., Moroni D., Nardini F. M., Rinzivillo S., Vadicamo L.
The ISTI Young Researcher Award is an award for young people of Institute of Information Science and Technologies (ISTI) with high scientific production. In particular, the award is granted to young staff members (less than 35 years old) by assessing the yearly scientific production of the year preceding the award. This report documents procedure and results of the 2017 edition of the award.Source: ISTI Technical reports, 2017

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2017 Report Closed Access

OSIRIS - Assi principali d'inerzia per la valutazione delle misure esterne e della direzione di una nave rilevata da una mappa SAR
Bedini L., Righi M., Salerno E.
Based on the consideration that the principal inertia axes in a SAR image representing a vessel roughly coincide with the fore-to-aft and the port-to-starboard lines, we describe a method to evaluate the size and heading of the vessel. In presence of the typical artifacts affecting SAR images, our method is capable of isolating well the vessel footprint, so to enable us to estimate the vessel's length overall and beam overall, as well as its relevant radiometric features. This is a preparatory work to the ship classification module to be integrated in the OSIRIS system. OSIRIS (Optical/SAR data and system Integration for Rush Identification of Ship models) is a technology project supported by the European space agency.Source: Project report, OSIRIS, 2017

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2017 Report Closed Access

OSIRIS - Segmentation, ship identification and ship size estimation from high-resolution SAR imagery
Bedini L., Righi M., Salerno E.
This report summarizes our proposals and results on problems posed by the software module 2 (Ship Classification, or SC) of the OSIRIS system. From the UML specification, the computational part of this module includes five phases: a) Segmentation; b) Shape recognition; c) Size estimation; d) Ship classification; e) Final estimation. Phases d) and e) have been assigned to an advanced classification submodule based on a ground-truth database, already devised in Salerno (2016), which will be the subject of a separate report. In the following, we deal with Segmentation-Shape recognition and Size estimation, where ``shape recognition'' means identifying the component of the segmented image that most likely contains the SAR ship footprint. The keys to the proposed processing are an adaptive-threshold segmentation followed by a maximum-area connected component detection, and the identification of the fore-and-aft line of the ship as the axis of minimum inertia with respect to the connected component barycenter. Once this axis has been found, the size-estimation phase is intended to find the ship length overall and beam overall. Our solution to this problem is to approximate a minimum-area rectangle enclosing the target and leaving out as many artifacts as possible. To this end, we devised two iterative strategies, taking into account that a ship has normally a well-defined, not general, shape. The principal inertia axis at the last iteration is also an estimate of the ship heading with a 180-degree ambiguity.Source: Project report, OSIRIS, 2017

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2017 Report Closed Access

OSIRIS - Segmentazione di immagini SAR
Bedini L., Righi M., Salerno E.
In questo lavoro viene descritto il metodo SISS (Ship Image Segmentation from SAR). Il metodo segmenta le navi che sono presenti nelle immagini provenienti da Synthetic Aperture Radar (SAR) installato su satelliti. Il metodo calcola un'approssimazione della sagoma della nave presente nell'immagine elaborata. Se nell'immagine è presente più di una nave, elabora la sagoma della nave che riflette maggiormente il segnale radar inviato. In particolare, il metodo è in grado di filtrare il rumori e i disturbi derivanti da sidelobe e speckle. Le immagini analizzate devono contenere, oltre alla nave da elaborare, una porzione di mare intorno a essa per calcolare il background. In un'immagine SAR, sia essa a bassa o alta risoluzione, quando un oggetto "riflettente" come il metallo di una nave è "illuminato", ci aspettiamo che rifletta una quantità omogenea di segnale radio maggiore rispetto all'ambiente che lo circonda. Inoltre, la nave è un oggetto connesso e quindi, fatta eccezione per parti radiotrasparenti, il segnale riflesso dalla nave e registrato dall'antenna ricevente è rappresentabile come un'area connessa. In caso che vi siano alcune aree radioriflettenti separate da aree radiotrasparenti, saranno visibili insiemi di aree connesse a distanza ravvicinata. In questo caso, poiché spesso nelle navi il segnale è riflesso dalle strutture di poppa e prua, il metodo SISS raccorda queste aree. Precisiamo che SISS attenua i disturbi dei lobi laterali che sono in saturazione, la loro eliminazione è demandata a un successivo processo di calcolo. L'innovazione introdotta da SISS consiste nella velocità di calcolo e nell'uso di seguito descritto di metodi statistici per l'eliminazione degli outlayer. SISS è stato implementato e testato su 30 immagini reali: 20 immagini acquisite dal satellite Sentinel 1 e 10 immagini acquisite dal satellite COSMO-SkyMed.Source: Project report, OSIRIS, 2017

See at: CNR ExploRA Restricted


2017 Journal article Open Access OPEN

Bayesian Volterra system identification using reversible jump MCMC algorithm
Karakus O., Kuruoglu E. E., Altinkaya M. A.
Volterra systems have had significant success in modelling nonlinear systems in various real-world applications. However, it is generally assumed that the nonlinearity degree of the system is known beforehand. In this paper, we contribute to the literature on Volterra system identification (VSI) with a numerical Bayesian approach which identifies model coefficients and the nonlinearity degree concurrently. Although this numerical Bayesian method, namely reversible jump Markov chain Monte Carlo (RJMCMC) algorithm has been used with success in various model selection problems, our use is in a novel context in the sense that both memory size and nonlinearity degree are estimated. The aforementioned study ensures an anomalous approach to RJMCMC and provides a new understanding on its flexible use which enables trans-structural transitions between different classes of models in addition to transdimensional transitions for which it is classically used. We study the performance of the method on synthetically generated data including OFDM communications over a nonlinear channel.Source: Signal processing (Print) 141 (2017): 125–136. doi:10.1016/j.sigpro.2017.05.031
DOI: 10.1016/j.sigpro.2017.05.031

See at: DSpace@IZTECH Open Access | Signal Processing Open Access | ISTI Repository Open Access | Signal Processing Restricted | Signal Processing Restricted | Signal Processing Restricted | Signal Processing Restricted | CNR ExploRA Restricted | Signal Processing Restricted | Signal Processing Restricted


2017 Journal article Open Access OPEN

Algae through the looking glass
Coltelli P., Barsanti L., Evangelista V., Gualtieri P.
Microalgae are one of the most suitable subjects for testing the potentiality of light microscopy and image analysis, because of the size of single cells, their endogenous chromaticity, and their metabolic and physiological characteristics. Microscope observations and image analysis can use microalgal cells from lab cultures or collected from water bodies as model to investigate metabolic processes, behavior/reaction of cells under chemical or photic stimuli, and dynamics of population in the natural environment in response to changing conditions. In this paper we will describe the original microscope we set up together with the image processing techniques we improved to deal with these topics. Our system detects and recognizes in-focus cells, extracts their features, measures cell concentration in multi-algal samples, reconstructs swimming cell tracks, monitors metabolic processes, and measure absorption and fluorescent spectra of subcellular compartments. It can be used as digital microscopy station for algal cell biology and behavioral studies, and field analysis applications.Source: Microscopy research and technique (Print) 80 (2017): 486–494. doi:10.1002/jemt.22820
DOI: 10.1002/jemt.22820

See at: ISTI Repository Open Access | Microscopy Research and Technique Restricted | Microscopy Research and Technique Restricted | Microscopy Research and Technique Restricted | onlinelibrary.wiley.com Restricted | Microscopy Research and Technique Restricted | Microscopy Research and Technique Restricted | CNR ExploRA Restricted


2017 Contribution to conference Open Access OPEN

3D Chromatin structure estimation from chromosome conformation capture data
Caudai C., Salerno E., Zoppè M., Tonazzini A.
In this communication we describe ChromStruct4, a method to reconstruct a set of plausible chromatin configurations starting from contact data obtained through Chromosome Conformation Capture techniques. Chromating fibre is modeled as a kinematic chain made of consecutive and partially penetrable beads whose properties (bead size, elasticity, curvature, etc.) can be suitably constrained. The chain can be divided in segments corresonding to Topological Association Domains. We do not search for a unique consensus configuration, because the experimental data are not derived from a single cell, but from millions of cells. We use a coarse-grained recoursive approach, based on a Simulated Annealing algorithm in order to sample the solution space. As opposed to most popular methods, we do not translate contact frequencies deterministically into distances, since this often produces structures that are not consistent with the Euclidean geometry, but adopt the assumption that loci with very high contact frequencies are actually close, but loci with low contact frequencies are not necessarily far away. ChromStruct4 is tested against real Hi-C data and compared with other methods for the 3-dimesional reconstruction fo Chromatin structure starting from Chromosome Conformation Capture data.Source: BITS 2017 - 14th Annual Meeting of the Bioinformatics Italian Society, Cagliari, Italy, 5-7 July 2017

See at: ISTI Repository Open Access | CNR ExploRA Open Access


2017 Journal article Open Access OPEN

Envisat RA-2 individual echoes: a unique dataset for a better understanding of inland water altimetry potentialities
Abileah R., Scozzari A., Vignudelli S.
The exploitation of synthetic aperture properties in nadir-looking radars is opening new scenarios in the framework of satellite radar altimetry. Both recent and upcoming missions including Cryosat-2, Sentinel-3, Sentinel-6 and SWOT take benefit from the coherent processing of radar data, aimed at improving range measurements in particular contexts, such as ice, open ocean, coastal zone, and even inland waters. This work investigates the possibilities offered by current and future satellite radar altimetry missions for the study of inland water bodies, probing into the peculiarities of the expected radar returns and their potential usage. In this regard, signals collected by the RA-2 instrument (Radar Altimeter 2) onboard the Envisat mission offer an unprecedented possibility, even with a relatively low pulse repetition frequency, to analyze the peculiarities of actual signals for detecting and ranging small water surfaces. In particular, the RA-2 instrument offers a global archive of Individual Echoes (IEs), collected at the native sampling rate of 1795 Hz, in addition to the 18 Hz data obtained by incoherent averaging, which are typically delivered to the users as standard products. RA-2 shares with future radar platforms such as Sentinel-6 a continuous and interleaved working modality, as was recommended by the scientific community in designing next missions' requirements. This is a further reason to consider the usage of RA-2 IEs as particularly attractive. Whilst only available for a small percentage of the earth's surface, sufficient IE data exist to study the height retrieval capability of these echoes, in particular for what concerns small water bodies, where we show that enough coherence is exhibited for focusing relatively narrow surfaces and range them correctly. A peculiar aspect of this work lies in the assumption that most of the returned echoes (in RA-2 IEs) are specular. A theoretical framework is developed according to this assumption, which is validated by investigating real RA-2 data and observing their related specular features. In particular, we discuss how specular echoes are expected to be very common in inland altimetry, and are most often associated with small to medium size lakes and rivers. This paper illustrates the expected electromagnetic behavior of specular water targets by exploiting the classical radar cross-section (RCS) theory for specular surfaces. Results from the model are compared with real IE data in three selected case studies, regarding two rivers of variable width and one flood plain, in order to check different hydrological regimes. The model very closely matches the data in all cases, making the results of this validation activity very promising. In particular, we demonstrate the feasibility of using satellite radar altimetry in rivers much smaller than what was considered possible until nowSource: Remote sensing (Basel) 9 (2017): 605. doi:10.3390/rs9060605
DOI: 10.3390/rs9060605

See at: Remote Sensing Open Access | Remote Sensing Open Access | Remote Sensing Open Access | CNR ExploRA Open Access | Remote Sensing Open Access | Remote Sensing Open Access | Remote Sensing Open Access | Remote Sensing Open Access


2017 Report Closed Access

OSIRIS - Satellite SAR imagery processing for vessel kinematics estimation
Reggiannini M.
Navigating vessels detection, identification and kinematics parameters estimation are relevant tasks concerning maritime surveillance and monitoring. One way to perform such operations is to process maps captured by Synthetic Aperture Radar (SAR) sensors installed on board of satellite constellations orbiting around earth-centered trajectories. Navigating vessels leave traces of their motion in the form of wake patterns on the water surface. Wakes are visible in high resolution SAR maps and bear information related to the kinematic variables of the vessel motion. A proper processing of the wake system allows to estimate the orientation of the vessel motion and the velocity module. This information can be exploited in the implementation of decision procedures dedicated to the control of maritime traffic. This document describes the design and implementation of software procedures with the purpose of estimating the motion parameters of a navigating vessel, through the processing of the wake pattern generated by the vessel itself.Source: Project report, OSIRIS, 2017

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2017 Conference article Open Access OPEN

Nonlinear model selection for PARMA processes using RJMCMC
Karakuå? O., Kuruoglu E. E., Altinkaya M. A.
Many prediction studies using real life measurements such as wind speed, power, electricity load and rainfall utilize linear autoregressive moving average (ARMA) based models due to their simplicity and general character. However, most of the real life applications exhibit nonlinear character and modelling them with linear time series may become problematic. Among nonlinear ARMA models, polynomial ARMA (PARMA) models belong to the class of linear-in-the-parameters. In this paper, we propose a reversible jump Markov chain Monte Carlo (RJMCMC) based complete model estimation method which estimates PARMA models with all their parameters including the nonlinearity degree. The proposed method is unique in the manner of estimating the nonlinearity degree and all other model orders and model coefficients at the same time. Moreover, in this paper, RJMCMC has been examined in an anomalous way by performing transitions between linear and nonlinear model spaces.Source: EUSIPCO 25th European Signal Processing Conference, Kos, Greece, 28 August - 2 September 2017
DOI: 10.23919/eusipco.2017.8081571
DOI: 10.5281/zenodo.1159433
DOI: 10.5281/zenodo.1159434

See at: DSpace@IZTECH Open Access | openaccess.iyte.edu.tr Open Access | ZENODO Open Access | academic.microsoft.com Restricted | dblp.uni-trier.de Restricted | ieeexplore.ieee.org Restricted | CNR ExploRA Restricted | xplorestaging.ieee.org Restricted