163 citations · 1.5k across the 45 of their papers we have counts for
46 papers
Bootstrap Pettitt test for detecting change point in hydroclimatological data: a case study for Itaipu hydroelectric plant in Brazil
Luiza Chiarelli Conte, Débora Missio Bayer, Fábio M. Bayer
The Pettitt test has been widely used in climate change and hydrological analyzes. However, studies evidence difficulties of this test in detecting change points, especially in sma…
Fast Data-independent KLT Approximations Based on Integer Functions
A. P. Radünz, D. F. G. Coelho, F. M. Bayer +2
The Karhunen-Loève transform (KLT) stands as a well-established discrete transform, demonstrating optimal characteristics in data decorrelation and dimensionality reduction. Its ab…
Extensions on Low-complexity DCT Approximations for Larger Blocklengths Based on Minimal Angle Similarity
A. P. Radünz, L. Portella, R. S. Oliveira +2
The discrete cosine transform (DCT) is a central tool for image and video coding because it can be related to the Karhunen-Loève transform (KLT), which is the optimal transform in…
An Iterative Wavelet Threshold for Signal Denoising
F. M. Bayer, A. J. Kozakevicius, R. J. Cintra
This paper introduces an adaptive filtering process based on shrinking wavelet coefficients from the corresponding signal wavelet representation. The filtering procedure considers…
Low-complexity Multidimensional DCT Approximations
V. A. Coutinho, R. J. Cintra, F. M. Bayer
In this paper, we introduce low-complexity multidimensional discrete cosine transform (DCT) approximations. Three dimensional DCT (3D DCT) approximations are formalized in terms of…
2-D Rayleigh Autoregressive Moving Average Model for SAR Image Modeling
B. G. Palm, F. M. Bayer, R. J. Cintra
Two-dimensional (2-D) autoregressive moving average (ARMA) models are commonly applied to describe real-world image data, usually assuming Gaussian or symmetric noise. However, rea…
Improved Point Estimation for the Rayleigh Regression Model
B. G. Palm, F. M. Bayer, R. J. Cintra
The Rayleigh regression model was recently proposed for modeling amplitude values of synthetic aperture radar (SAR) image pixels. However, inferences from such model are based on t…
Signal Detection and Inference Based on the Beta Binomial Autoregressive Moving Average Model
B. G. Palm, F. M. Bayer, R. J. Cintra
This paper proposes the beta binomial autoregressive moving average model (BBARMA) for modeling quantized amplitude data and bounded count data. The BBARMA model estimates the cond…
Low-Complexity Loeffler DCT Approximations for Image and Video Coding
D. F. G. Coelho, R. J. Cintra, F. M. Bayer +6
This paper introduced a matrix parametrization method based on the Loeffler discrete cosine transform (DCT) algorithm. As a result, a new class of eight-point DCT approximations wa…
DCT Approximations Based on Chen's Factorization
C. J. Tablada, T. L. T. da Silveira, R. J. Cintra +1
In this paper, two 8-point multiplication-free DCT approximations based on the Chen's factorization are proposed and their fast algorithms are also derived. Both transformations ar…
Wavelength-Resolution SAR Ground Scene Prediction Based on Image Stack
B. G. Palm, D. I. Alves, M. I. Pettersson +6
This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images. The GSP image can be used a…
Rayleigh Regression Model for Ground Type Detection in SAR Imagery
B. G. Palm, F. M. Bayer, R. J. Cintra +2
This letter proposes a regression model for nonnegative signals. The proposed regression estimates the mean of Rayleigh distributed signals by a structure which includes a set of r…
Fast Radix-32 Approximate DFTs for 1024-Beam Digital RF Beamforming
A. Madanayake, R. J. Cintra, N. Akram +6
The discrete Fourier transform (DFT) is widely employed for multi-beam digital beamforming. The DFT can be efficiently implemented through the use of fast Fourier transform (FFT) a…
Towards a Low-SWaP 1024-beam Digital Array: A 32-beam Sub-system at 5.8 GHz
Arjuna Madanayake, Viduneth Ariyarathna, Suresh Madishetty +8
Millimeter wave communications require multibeam beamforming in order to utilize wireless channels that suffer from obstructions, path loss, and multi-path effects. Digital multibe…
Autoregressive Model for Multi-Pass SAR Change Detection Based on Image Stacks
B. G. Palm, D. I. Alves, V. T. Vu +6
Change detection is an important synthetic aperture radar (SAR) application, usually used to detect changes on the ground scene measurements in different moments in time. Tradition…
A Class of Low-complexity DCT-like Transforms for Image and Video Coding
T. L. T. da Silveira, D. R. Canterle, D. F. G. Coelho +3
The discrete cosine transform (DCT) is a relevant tool in signal processing applications, mainly known for its good decorrelation properties. Current image and video coding standar…
Data-independent Low-complexity KLT Approximations for Image and Video Coding
A. P. Radünz, T. L. T. da Silveira, F. M. Bayer +1
The Karhunen-Loève transform (KLT) is often used for data decorrelation and dimensionality reduction. The KLT is able to optimally retain the signal energy in only few transform co…
A Multiparametric Class of Low-complexity Transforms for Image and Video Coding
D. R. Canterle, T. L. T. da Silveira, F. M. Bayer +1
Discrete transforms play an important role in many signal processing applications, and low-complexity alternatives for classical transforms became popular in recent years. Particul…
Modeling the Temporal Population Distribution of Ae. aegypti Mosquito using Big Earth Observation Data
Oladimeji Mudele, Fabio M. Bayer, Lucas Zanandrez +2
Over 50% of the world population is at risk of mosquito-borne diseases. Female Ae. aegypti mosquito species transmit Zika, Dengue, and Chikungunya. The spread of these diseases cor…
Low-complexity 8-point DCT Approximation Based on Angle Similarity for Image and Video Coding
R. S. Oliveira, R. J. Cintra, F. M. Bayer +3
The principal component analysis (PCA) is widely used for data decorrelation and dimensionality reduction. However, the use of PCA may be impractical in real-time applications, or…
Beta Autoregressive Fractionally Integrated Moving Average Models
Guilherme Pumi, Marcio Valk, Cleber Bisognin +2
In this work we introduce the class of beta autoregressive fractionally integrated moving average models for continuous random variables taking values in the continuous unit interv…
Beta seasonal autoregressive moving average models
Fábio M. Bayer, Renato J. Cintra, Francisco Cribari-Neto
In this paper we introduce the class of beta seasonal autoregressive moving average (SARMA) models for modeling and forecasting time series data that assume values in the standa…
Beta regression control chart for monitoring fractions and proportions
Fábio Mariano Bayer, Catia Michele Tondolo, Fernanda Maria Müller
Regression control charts are usually used to monitor variables of interest that are related to control variables. However, for fraction and/or proportion data, the use of standard…
Kumaraswamy autoregressive moving average models for double bounded environmental data
Fábio Mariano Bayer, Débora Missio Bayer, Guilherme Pumi
In this paper we introduce the Kumaraswamy autoregressive moving average models (KARMA), which is a dynamic class of models for time series taking values in the double bounded inte…