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Found 36 papers, 1 papers with code
Discrete Fourier Transform Approximations Based on the Cooley-Tukey Radix-2 Algorithm
This report elaborates on approximations for the discrete Fourier transform by means of replacing the exact Cooley-Tukey algorithm twiddle-factors by low-complexity integers, such as $0, \pm \frac{1}{2}, \pm 1$.
Low-complexity Multidimensional DCT Approximations
In general, the suggested methods showed competitive performance at a considerably lower computational cost.
Improved Point Estimation for the Rayleigh Regression Model
The Rayleigh regression model was recently proposed for modeling amplitude values of synthetic aperture radar (SAR) image pixels.
Low-complexity Approximate Convolutional Neural Networks
The idea is to approximate all elements of a given ConvNet and replace the original convolutional filters and parameters (pooling and bias coefficients; and activation function) with efficient approximations capable of extreme reductions in computational complexity.
Robust Rayleigh Regression Method for SAR Image Processing in Presence of Outliers
The presence of outliers (anomalous values) in synthetic aperture radar (SAR) data and the misspecification in statistical image models may result in inaccurate inferences.
Low-Complexity Loeffler DCT Approximations for Image and Video Coding
This paper introduced a matrix parametrization method based on the Loeffler discrete cosine transform (DCT) algorithm.
DCT Approximations Based on Chen's Factorization
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.
Prediction Intervals in the Beta Autoregressive Moving Average Model
In this paper, we propose five prediction intervals for the beta autoregressive moving average model.
Wavelength-Resolution SAR Ground Scene Prediction Based on Image Stack
This paper presents five different statistical methods for ground scene prediction (GSP) in wavelength-resolution synthetic aperture radar (SAR) images.
Towards a Low-SWaP 1024-beam Digital Array: A 32-beam Sub-system at 5.8 GHz
Arithmetic complexity due to multiplication is reduced from the FFT complexity of $\mathcal{O}(N\: \log N)$ for DFT realizations, down to zero, thus yielding a 46% and 55% reduction in chip area and dynamic power consumption, respectively, for the $N=32$ case considered.
Fast Radix-32 Approximate DFTs for 1024-Beam Digital RF Beamforming
These approximate DFT (ADFT) algorithms have significantly reduced circuit complexity and power consumption compared to traditional FFT approaches while trading off a subtle loss in computational precision which is acceptable for digital beamforming applications in RF antenna implementations.
Autoregressive Model for Multi-Pass SAR Change Detection Based on Image Stacks
Applying AR model for each pixel position in the image stack, we obtained an estimated image of the ground scene which can be used as a reference image for CDA.
The Gamma Generalized Normal Distribution: A Descriptor of SAR Imagery
We propose a new four-parameter distribution for modeling synthetic aperture radar (SAR) imagery named the gamma generalized normal (GGN) by combining the gamma and generalized normal distributions.
Efficient and Self-Recursive Delay Vandermonde Algorithm for Multi-Beam Antenna Arrays
An efficient DVM algorithm is proposed to reduce the complexity of radio-frequency (RF) $N$-beam analog beamforming systems.
Radix-2 Self-Recursive Sparse Factorizations of Delay Vandermonde Matrices for Wideband Multi-Beam Antenna Arrays
This paper presents a self-contained factorization for the Vandermonde matrices associated with true-time delay based wideband analog multi-beam beamforming using antenna arrays.
A Class of Low-complexity DCT-like Transforms for Image and Video Coding
The novel transforms perform close to or outperform the current state-of-the-art DCT approximations.
Low-complexity Three-dimensional Discrete Hartley Transform Approximations for Medical Image Compression
In this work, we present a set of multiplierless DHT approximations, which can be implemented with fixed-point arithmetic.
Data-independent Low-complexity KLT Approximations for Image and Video Coding
The Karhunen-Lo\`eve transform (KLT) is often used for data decorrelation and dimensionality reduction.
Low-complexity Rounded KLT Approximation for Image Compression
Because its computation depends on the matrix of covariances of the input signal, the use of the KLT in real-time applications is severely constrained by the difficulty in developing fast algorithms to implement it.
Von Mises Tapering: A New Circular Windowing
Discrete and continuous standard windowing are revisited and a a new taper is introduced, which is derived from the normal circular distribution by von Mises.
Low-complexity Scaling Methods for DCT-II Approximations
This paper introduces a collection of scaling methods for generating $2N$-point DCT-II approximations based on $N$-point low-complexity transformations.
Geometrical Representation for Number-theoretic Transforms
This short note introduces a geometric representation for binary (or ternary) sequences.
Information Theory Signal Processing Information Theory
Low-complexity Architecture for AR(1) Inference
In this Letter, we propose a low-complexity estimator for the correlation coefficient based on the signed $\operatorname{AR}(1)$ process.
Rounded Hartley Transform: A Quasi-involution
A new multiplication-free transform derived from DHT is introduced: the RHT.
An Integer Approximation Method for Discrete Sinusoidal Transforms
Approximate methods have been considered as a means to the evaluation of discrete transforms.
A Multiparametric Class of Low-complexity Transforms for Image and Video Coding
Particularly, the discrete cosine transform (DCT) has proven to be convenient for data compression, being employed in well-known image and video coding standards such as JPEG, H. 264, and the recent high efficiency video coding (HEVC).
Multidimensional Wavelets for Scalable Image Decomposition: Orbital Wavelets
New orbital 2D-wavelets are introduced for the decomposition of still images, showing that it is possible to perform an analysis simultaneous in two distinct scales.
Low-complexity 8-point DCT Approximation Based on Angle Similarity for Image and Video Coding
Practical applications in image and video coding demonstrate the relevance of the proposed transformation.
DCT-like Transform for Image Compression Requires 14 Additions Only
A low-complexity 8-point orthogonal approximate DCT is introduced.
Multimedia Data Structures and Algorithms Applications Computation
Low-complexity Image and Video Coding Based on an Approximate Discrete Tchebichef Transform
Image and video compression simulations in popular standards shows good performance of the proposed transform.
Multiplierless 16-point DCT Approximation for Low-complexity Image and Video Coding
An orthogonal 16-point approximate discrete cosine transform (DCT) is introduced.
A Class of DCT Approximations Based on the Feig-Winograd Algorithm
A new class of matrices based on a parametrization of the Feig-Winograd factorization of 8-point DCT is proposed.
A Discrete Tchebichef Transform Approximation for Image and Video Coding
In this paper, we introduce a low-complexity approximation for the discrete Tchebichef transform (DTT).
Improved 8-point Approximate DCT for Image and Video Compression Requiring Only 14 Additions
The proposed transform possesses low computational complexity and is compared to state-of-the-art DCT approximations in terms of both algorithm complexity and peak signal-to-noise ratio.
A DCT Approximation for Image Compression
An orthogonal approximation for the 8-point discrete cosine transform (DCT) is introduced.
A Multiplierless Pruned DCT-like Transformation for Image and Video Compression that Requires 10 Additions Only
A multiplierless pruned approximate 8-point discrete cosine transform (DCT) requiring only 10 additions is introduced.
