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Search results for: MULTIVARIATE LINEAR REGRESSION
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Decisional DNA with embedded Relief-F linear regression for knowledge and experience management
PublicationOmowiono zastowania Decyzyjnego DNA, regresji liniowej oraz funkcji RELIEF-F w procesach formalnego modelowania i wspomagania zarzadzania wiedza oraz zarzadzania doswiadczeniem.
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Prediction of Peptide Retention at Different HPLC Conditions from Multiple Linear Regression Models
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Application of Multivariate Adaptive Regression Splines (MARSplines) Methodology for Screening of Dicarboxylic Acids Cocrystal Using 1D and 2D Molecular Descriptors
PublicationDicarboxylic acids (DiAs) are probably one of the most popular cocrystals formers. Due to the high hydrophilicity and non-toxicity, they are promising solubilizes of active pharmaceutical ingredients (APIs). Although DiAs appear to be highly capable of forming multicomponent crystals with various compounds, some systems reported in the literature are physical mixtures the solid state without forming stable intermolecular complex....
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Application of Multivariate Adaptive Regression Splines (MARSplines) for Predicting Hansen Solubility Parameters Based on 1D and 2D Molecular Descriptors Computed from SMILES String
PublicationA new method of Hansen solubility parameters (HSPs) prediction was developed by combining the multivariate adaptive regression splines (MARSplines) methodology with a simple multivariable regression involving 1D and 2D PaDEL molecular descriptors. In order to adopt the MARSplines approach to QSPR/QSAR problems, several optimization procedures were proposed and tested. The effectiveness of the obtained models was checked via standard...
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Prediction of skin color, tanning and freckling from DNA in Polish population: linear regression, random forest and neural network approaches
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Novel liquid chromatography method based on linear weighted regression for the fast determination of isoprostane isomers in plasma samples using sensitive tandem mass spectrometry detection
PublicationA simple, fast, sensitive and accurate methodology based on a LLE followed by liquid chromatography–tandem mass spectrometry for simultaneous determination of four regioisomers (8-iso prostaglandin F2α, 8-iso-15(R)-prostaglandin F2α, 11β-prostaglandin F2α, 15(R)-prostaglandin F2α) in routine analysis of human plasma samples was developed. Isoprostanes are stable products of arachidonic acid peroxidation and are regarded as the...
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SZACOWANIE ZAWARTOŚCI BENZO(a)PIRENU W PYLE ZAWIESZONYM PM10 W AGLOMERACJI TRÓJMIEJSKIEJ ZA POMOCĄ WIELOWYMIAROWEJ REGRESJI LINIOWEJ=ESTIMATION OF BENZO(A)PYRENE CONTENT IN SUSPENDED DUST PM10 IN TRI-CITY AGGLOMERATION USING MULTIDIMENSIONAL LINEAR REGRESSION
PublicationW pracy przedstawiono próbę oszacowania przy pomocy wielowymiarowej regresji liniowej modelu empirycznego opisującego czynniki wpływające na zawartość B(a)P w pyle zawieszonym PM10 w Aglomeracji Trójmiejskiej w latach 2008-2011. Na przestrzeni tych lat średnioroczne stężenie B(a)P w PM10 wzrosło ponad dwukrotnie i ponad trzykrotnie przewyższa poziom docelowy. Z przeprowadzonych analiz wynika, że główną przyczyną wzrostu stężenia...
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Liniowe i nieliniowe modele wielowymiarowej kalibracji do predykcji stężenia substancji z pomiarów woltamperometrycznych
PublicationPomiary woltamperometryczne znajdują zastosowanie w wielu dziedzinach nauki i techniki, np. w przemyśle farmaceutycznym. Dane uzyskane w wyniku takich pomiarów zawierają informację odnośnie rodzaju i stężenia badanej substancji, jednakże są one często kłopotliwe w bezpośredniej interpretacji. Z tego powodu, istnieje konieczność wykorzystania odpowiednich metod matematycznych, które umożliwiają uzyskanie bezpośredniej i precyzyjnej...
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Qualitative and Quantitative Analysis of Selected Tonic Waters by Potentiometric Taste Sensor With All-Solid-State Electrodes
PublicationTaste sensor with five all-solid-state electrodes (ASSE) III (third version) was used for qualitative and quantitative analysis of selected tonic waters (J.Gasco, Kinley, Jurajski, Jurajski with citrus flavor, Carrefour, Schweppes Indian Tonic, and Schweppes Bitter Lemon). The results obtained by this taste sensor analyzed with principal component analysis, agglomerative hierarchical clustering methods show that this sensor can...
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Application of Multivariate Analysis Methods in Welding Engineering
PublicationPhenomena and processes taking place during welding are usually very complex and, for this reason, should be described using multivariate methods. The article discusses the methodological basis and selected application areas as regards the solving of welding problems using statistical multivariate methods. In addition, the article presents exemplary applications of the design of experiment, multiple regression analysis, cluster...
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Predicting Value of Binding Constants of Organic Ligands to Beta-Cyclodextrin: Application of MARSplines and Descriptors Encoded in SMILES String
PublicationThe quantitative structure–activity relationship (QSPR) model was formulated to quantify values of the binding constant (lnK) of a series of ligands to beta–cyclodextrin (β-CD). For this purpose, the multivariate adaptive regression splines (MARSplines) methodology was adopted with molecular descriptors derived from the simplified molecular input line entry specification (SMILES) strings. This approach allows discovery of regression...
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On-line assessment of oil quality during deep frying using an electronic nose and proton transfer reaction mass spectrometry
PublicationWe describe a novel method for the quality assessment of oil utilized for deep frying. The method is based on the analysis of frying fumes using a custom electronic nose. The quality score could be obtained after less than 3 min of analysis and without interrupting the frying process or sampling the oil directly. The obtained results were correlated with the peroxide value using a multivariate linear regression model. The most...
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Fading Modeling in Maritime Container Terminal Environments
PublicationIn this paper, an analytical model for slow and fast fading effects in maritime container terminals is derived, from fitting distributions to the results of measurements performed in an actual operational environment. The proposed model is composed of a set of equations, enabling to evaluate fading statistical distribution parameters for different system and environments conditions, as a function of frequency, base station antenna...
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Dependent self-employed individuals: are they different from paid employees?
PublicationThis study focuses on dependent self-employment, which covers a situation where a person works for the same employer as a typical worker while on a self-employment contractual basis, i.e., without a traditional employment contract and without certain rights granted to "regular" employees. The research exploits the individual-level dataset of 35 European countries extracted from the 2017 edition of the European Labour Force Survey...
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Fuzzy regresion approach to road safety analysis at regional level
PublicationRoad safety modelling on regional level of NUTS 2 in the EU is the complex issue and authors of this article indicate this in previous publications. NUTS 2 are basic regions for the application of regional policies (0.8-3 m inhabitants). During multivariate models development they discovered that it is difficult to make regression model well described all regions, even if they are from one country. In the first step Poisson model...
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Statistics 2022_23
e-Learning Courses1.Elements of probability. The axioms of the probability theory 2. Random variables and their distributions. Discrete and continuous random variables 3. Parameters of random variables: expected value, moments 4. Selected distributions of random variables (Bernoulli, Poison, Gaussian) 5.The distribution in the sample. Visualisation by histograms 6. Measures of statistical location: arithmetic mean, median, quantiles. 7. Measures...
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Estimation of the Ultimate Strength of FRP Strips-to-Masonry Substrates Bond
PublicationFiber-Reinforced Polymers (FRP) were developed as a new method over the past decades due to their many beneficial mechanical properties, and they are commonly applied to strengthen masonry structures. In this paper, the Artificial Neural Network (ANN), K-fold Cross-Validation (KFCV) technique, Multivariate Adaptive Regression Spline (MARS) method, and M5 Model Tree (M5MT) method were utilized to predict the ultimate strength of...
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The influences of the information and communication technology on the structural changes of Japanese energy sectors from 1985 through 2005: a statistical analysis
PublicationThe purpose of this study is to analyse the influences of information and communication technology (ICT) on the structural changes of Japanese energy sectors from 1985-2005. In this study, ICT is represented by two explanatory variables, namely: 1) computers, main parts and accessories; 2) telecommunications equipment. We employ a statistical tool in investigating the influences quantitatively, namely constrained multivariate regression...
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Development and validation of a model that includes two ultrasound parameters and the plasma D-dimer level for predicting malignancy in adnexal masses: an observational study
PublicationBackground: Pre-operative discrimination of malignant from benign adnexal masses is crucial for planning additional imaging, preparation, surgery and postoperative care. This study aimed to define key ultrasound and clinical variables and develop a predictive model for calculating preoperative ovarian tumor malignancy risk in a gynecologic oncology referral center. We compared our model to a subjective ultrasound assessment (SUA)...
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Application of gas chromatographic data and 2D molecular descriptors for accurate global mobility potential prediction
PublicationMobility is a key feature affecting the environmental fate, which is of particular importance in the case of persistent organic pollutants (POPs) and emerging pollutants (EPs). In this study, the global mobility classification artificial neural networks-based models employing GC retention times (RT) and 2D molecular descriptors were constructed and validated. The high usability of RT was confirmed based on the feature selection...
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Electrochemical Production of Sodium Hypochlorite from Salty Wastewater Using a Flow-by Porous Graphite Electrode
PublicationThe production of sodium hypochlorite (NaOCl) from salty wastewater using an electrochemical cell has several advantages over other methods that often require hazardous chemicals and generate toxic waste, being more sustainable and environmentally friendly. However, the process of producing sodium hypochlorite using an electrochemical cell requires careful control of the operating conditions, such as the current density, flow rate,...
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An algorithm for selecting a machine learning method for predicting nitrous oxide emissions in municipal wastewater treatment plants
PublicationThis study presents an advanced algorithm for selecting machine learning (ML) models for nitrous oxide (N2O) emission prediction in wastewater treatment plants (WWTPs) employing the activated sludge process. The examined ML models comprised multivariate adaptive regression spline (MARS), support vector machines (SVM), and extreme gradient boosting (XGboost). The study explores the concept that involves new criteria to select the...
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Determination of benzo(a)pyrene content in PM10 using regression methods
PublicationThe paper presents an attempt of application of multidimensional linear regression to estimation of an empirical model describing the factors influencing on B(a)P content in suspended dust PM10 in Olsztyn and Elbląg city regions between 2010 and 2013. During this period annual average concentration of B(a)P in PM10 exceeded the admissible level 1.5-3 times. Conducted investigations confirm that the reasons of B(a)P concentration...
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On Noncausal Identification of Nonstationary Multivariate Autoregressive Processes
PublicationThe problem of identification of nonstationary multivariate autoregressive processes using noncausal local estimation schemes is considered and a new approach to joint selection of the model order and the estimation bandwidth is proposed. The new selection rule, based on evaluation of pseudoprediction errors, is compared with the previously proposed one, based on the modified Akaike’s final prediction error criterion.
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Classification and fingerprinting of kiwi and pomelo fruits by multivariate analysis of chromatographic and spectroscopic data
PublicationThe fingerprinting capacity of two analytical techniques, HPLC and UV-Vis spectroscopy in the case of fruits samples (kiwi and pomelo) has been investigated. The multivariate exploratory techniques were used for sample discrimination according to the fruit species and subspecies. The combination of principal component analysis with linear discriminant analysis is opening new directions in the fingerprinting analysis. The classifications...
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Efficiency of linear and non-linear classifiers for gas identification from electrocatalytic gas sensor
PublicationElectrocatalytic gas sensors belong to the family of electrochemical solid state sensors. Their responses are acquired in the form of I-V plots as a result of application of cyclic voltammetry technique. In order to obtain information about the type of measured gas the multivariate data analysis and pattern classification techniques can be employed. However, there is a lack of information in literature about application of such...
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Buried Object Characterization by Data-Driven Surrogates and Regression-Enabled Hyperbolic Signature Extraction
PublicationThis work addresses artificial-intelligence-based buried object characterization using FDTD-based electromagnetic simulation toolbox of a Ground Penetrating Radar (GPR) to generate B-scan data. In data collection, FDTD-based simulation tool, gprMax is used. The task is to estimate geophysical parameters of a cylindrical shape object of various radii, buried at different positions in the dry soil medium simultaneously and independently...
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JOURNAL OF MULTIVARIATE ANALYSIS
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Multivariate Behavioral Research
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Towards Designing an Innovative Industrial Fan: Developing Regression and Neural Models Based on Remote Mass Measurements
PublicationThis article presents the process of the construction and testing a remote, fully autonomous system for measuring the operational parameters of fans. The measurement results obtained made it possible to create and verify mathematical models using linear regression and neural networks. The process was implemented as part of the first stage of an innovative project. The article presents detailed steps of constructing a system to...
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublicationAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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Regression points in non-intrusive polynomial chaos expansion method and D-optimal design
PublicationThe paper addresses selected issues of uncertainty quantification in the modelling of a system containing surgical mesh used in ventral hernia repair. Uncertainties in the models occur e.g. due to variability of abdominal wall properties among others. In order to include them, a non-intrusive regression-based polynomial chaos expansion method is employed. Its accuracy depends on the choice of regression points. In the study a relation...
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Application of multivariate statistics in assessment of green analytical chemistry parameters of analytical methodologies
PublicationThe study offers a multivariate statistical analysis of a dataset, including the major metrological, “greenness” and methodological parameters of 43 analytical methodologies applied for aldrin determination (a frequently analyzed organic compound) in water samples. The variables (parameters) chosen were as follows: metrological (LOD, recovery, RSD), describing the “greenness” (amount of the solvent used, amount of waste generated)...
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Sensitivity analysis based on non-intrusive regression-based polynomial chaos expansion for surgical mesh modelling
PublicationThe modelling of a system containing implants used in ventral hernia repair and human tissue suffers from many uncertainties. Thus, a probabilistic approach is needed. The goal of this study is to define an efficient numerical method to solve non-linear biomechanical models supporting the surgeon in decisions about ventral hernia repair. The model parameters are subject to substantial variability owing to, e.g., abdominal wall...
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Multivariate analysis of impedance data obtained for coating systems of varying thickness applied on steel
PublicationElectrochemical impedance spectroscopy (EIS) has proven to be a valuable test method for the electrochemical characterization of protective coatings on metals. The common way of analysis in impedance spectroscopy is to model the impedance spectrum by means of an equivalent circuit and to extract the quantity of interest using optimization techniques. A model, corresponding to the behavior of the sample under testing, is important...
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Reducing Monitoring Costs in Industrially Contaminated Rivers: Cluster and Regression Analysis Approach
PublicationMonitoring contamination in river water is an expensive procedure, particularly for developing countries where pollution is a significant problem. This study was conducted to provide a pollution monitoring strategy that reduces the cost of laboratory analysis. The new monitoring strategy was designed as a result of cluster and regression analysis on field data collected from an industrially influenced river. Pollution sources in...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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LINEAR & MULTILINEAR ALGEBRA
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Regularized Local Multivariate Reduced-Order Models With Nonaffine Parameter Dependence
PublicationThis paper addresses a singular problem, not yet discussed in the literature, which occurs when parametric reduced-order models are created using a subspace projection approach with multiple concatenated projection bases. We show that this technique may lead to the appearance of localized artifacts in the frequency characteristics of a system, even when the reduced-order projection basis is rich enough to describe the original...
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Determinanty kreowania wartości marki poprzez media społecznościowe w gospodarce sieciowej
PublicationGłównym problemem badawczym podejmowanym w pracy, jest określenie struktury czynników determinujących kreowanie wartości marki w mediach społecznościowych. Dla rozwiązania tego problemu wykonano dwa badania. Pierwsze z nich dotyczyło określenia relacji pomiędzy wartością marki a jej pozycją w sieciach społecznościowych (model BV). Badanie to zrealizowano w oparciu o metody ilościowe: analizę statystyczną danych wtórnych i danych...
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Comparison of non-linear statical analysis of truss with linear and rotational side supports and 3d roof model
PublicationIn the paper geometrically non-linear analysis of example truss with linear and rotational elastic side supports is compared with geometrically non-linear analysis of part of the roof construction with purlins and truss-bracing. For different stiffness of side-supports a non linear relation between normal force in compressed chord due to out of truss plane displacement has been calculated.
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The need for linear revitalization. Gdynia case
PublicationThe aim of the article is to discuss the need of defining and implementation of the linear revitalization - the new approach related to the revitalization processes. The results of the preliminary investigations indicate that this kind of revitalization seems to be an important tool supporting city management and planning, especially in cases of cities fragmentation - causing lack of physical, social, economic and ecological cohesion....
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Programowanie Liniowe (Linear Programming)
e-Learning CoursesMateriały do przedmiotów: - Badania operacyjne (1/3), kier: informatyka mgr stac. rok. 1. sem. 1. - Operational research (1/3), kier: informatyka mgr stac. (ang) rok. 1. sem. 1. - Badania operacyjne (1/2), kier: informatyka mgr niestac. rok. 2. sem. 3.
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Application of Regression Line to Obtain Specified Number of Points in Reduced Large Datasets
PublicationModern measurement techniques like scanning technology or sonar measurements, provide large datasets, which are a reliable source of information about measured object, however such datasets are sometimes difficult to develop. Therefore, the algorithms for reducing the number of such sets are incorporated into their processing. In the reduction algorithms based on the...
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Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging
PublicationThe phenomenon of dynamic stall produce adverse aerodynamic loading which can adversely affect the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides an effective approach for delaying and mitigating dynamic stall characteristics without the addition of auxiliary system. ASO, however, requires multiple evaluations time-consuming computational fluid dynamics models. Metamodel-based...
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New semi-causal and noncausal techniques for detection of impulsive disturbances in multivariate signals with audio applications
PublicationThis paper deals with the problem of localization of impulsive disturbances in nonstationary multivariate signals. Both unidirectional and bidirectional (noncausal) detection schemes are proposed. It is shown that the strengthened pulse detection rule, which combines analysis of one-step-ahead signal prediction errors with critical evaluation of leave-one-out signal interpolation errors, allows one to noticeably improve detection results...
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Active Control of Highly Autocorrelated Machinery Noise in Multivariate Nonminimum Phase Systems
PublicationIn this paper, a novel multivariate active noise control scheme, designed to attenuate disturbances with high autocorrelation characteristics and preserve background signals, is proposed. The algorithm belongs to the class of feedback controllers and, unlike the popular feedforward FX-LMS approach, does not require availability of a reference signal. The proposed approach draws its inspiration from the iterative learning control...
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Positivity and job burnout in emergency personnel: examining linear and curvilinear relationship
PublicationThe aim of this study was to examine whether the relationship between the ratio of job-related positive to negative emotions (positivity ratio) and job burnout is best described as linear or curvilinear. Participants were 89 police officers (12% women) and 86 firefighters. The positivity ratio was evaluated using the Job-related Affective Wellbeing Scale (Van Katwyk, Fox, Spector, & Kelloway, 2000). Exhaustion and disengagement,...
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Lattice filter based multivariate autoregressive spectral estimation with joint model order and estimation bandwidth adaptation
PublicationThe problem of parametric, autoregressive model based estimation of a time-varying spectral density function of a multivariate nonstationary process is considered. It is shown that estimation results can be considerably improved if identification of the autoregressive model is carried out using the two-sided doubly exponentially weighted lattice algorithm which combines results yielded by two one-sided lattice algorithms running...
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Automated Design of Linear Phase Filters
PublicationThis paper presents a fast technique for an automated design of microwave filters with linear phase. The proposed method exploits the cost function defined using the location of complex zeros and poles of the filter’s transfer and reflection function. The effectiveness of the proposed technique is presented with two illustrative examples.