Search results for "Filter"
showing 10 items of 1019 documents
Particle Group Metropolis Methods for Tracking the Leaf Area Index
2020
Monte Carlo (MC) algorithms are widely used for Bayesian inference in statistics, signal processing, and machine learning. In this work, we introduce an Markov Chain Monte Carlo (MCMC) technique driven by a particle filter. The resulting scheme is a generalization of the so-called Particle Metropolis-Hastings (PMH) method, where a suitable Markov chain of sets of weighted samples is generated. We also introduce a marginal version for the goal of jointly inferring dynamic and static variables. The proposed algorithms outperform the corresponding standard PMH schemes, as shown by numerical experiments.
A fast recursive algorithm to compute local axial moments
2001
The paper describes a fast algorithm to compute local axial moments used in the algorithm of discrete symmetry transform (DST). The basic idea is grounded on fast recursive implementation of respective linear filters by using the so-called primitive kernel functions since the moment computation can be performed in the framework of linear filtering. The main result is that the computation of the local axial moments is independent of the kernel size, i.e. of the order O(1) per data point (pixel). This result is of relevance whenever the DST is used to face with real time computer vision problems. The experimental results confirm the time complexity predicted by the theory.
Signal-to-Noise Ratio in Bandpass Direct-Sequence Spread-Spectrum Modulation Systems
1982
The effects of a linear transmission channel on the performance of a correlator receiver for a direct-sequence spreadspectrum system are analyzed and a complete treatment of the influence of a periodic spreading code is carried out. The output data signal is obtained as a function of the channel characteristic and the code sequence employed; this allows maximizing the output signal level and evaluation of the influence of the synchronization error of the local code. The asymptotic value of the correlation loss has also been derived together with the intersymbol inteference power. The general expression of a figure of merit of the effectiveness of the system is also obtained in simple terms …
LabVIEW modeling and simulation, of the digital filters
2015
In order to study digital filters using virtual instrumentation a simulation program specifically designed for this purpose has been developed. To implement this program means to use the following facilities: studying digital Butterworth filters, Cebyshev, Bessel and Median and change their parameters: bandwidth, order, rank and slope; possibility of changing the input parameters: amplitude, offset and frequency; overlay over the input signal, to one of the types of noise such as white noise, Gaussian white noise and Poisson noise; choosing a type of digital filters: low pass, high pass, band-pass and band stop; waveforms graphical representation of the input and output signals; graphical r…
In-process tool-failure detection by means of AR models
1997
The present paper proposes a cutting tool breaking and chipping detection system for continuous and interrupted cutting, based on the analysis of the cutting force componentsFx andFy. A multifactorial experimental design has been carried out, to take account of the variability of the force signal. An adaptive signal processing algorithm is proposed, which detects catastrophic failure when at least one component deviates outside an estimated oscillation band for a time duration longer than a prefixed interval. The algorithm has been implemented on a four-microprocessor transputer board. Several tests confirmed the validity of the approach for detecting breaking and chipping phenomena in a fe…
Blind source separation for OFDM with filtering colored noise out
2011
Two blind algorithms that are developed with the intention of improving the symbol detection of Orthogonal Frequency Division Multiplexing (OFDM) techniques are proposed in this paper. OFDM systems are easy to equalize in implementations. The schemes are based on the theories of blind source separation (BSS). They are among the premier mechanisms used for extracting unobserved signals from observed mixtures in signal processing. In this study noise component of the received signal mixture is tried to be filtered out. A scalar energy function with the iterative fixed point rule for receive signal is used in determining the filter coefficients while taking the time correlation properties of t…
On the Design of Fast Wavelet Transform Algorithms With Low Memory Requirements
2008
In this paper, a new algorithm to efficiently compute the two-dimensional wavelet transform is presented. This algorithm aims at low memory consumption and reduced complexity, meeting these requirements by means of line-by-line processing. In this proposal, we use recursion to automatically place the order in which the wavelet transform is computed. This way, we solve some synchronization problems that have not been tackled by previous proposals. Furthermore, unlike other similar proposals, our proposal can be straightforwardly implemented from the algorithm description. To this end, a general algorithm is given which is further detailed to allow its implementation with a simple filter bank…
Anamorphic fractional Fourier transform: optical implementation and applications
1995
An additional degree of freedom is introduced to fractional-Fourier-transform systems by use of anamorphic optics. A different fractional Fourier order along the orthogonal principal directions is performed. A laboratory experimental system shows preliminary results that demonstrate the proposed theory. Applications such as anamorphic fractional correlation and multiplexing in fractional domains are briefly suggested.
Support Vector Machines Framework for Linear Signal Processing
2005
This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…
A Novel Approach to Introducing Adaptive Filters Based on the LMS Algorithm and Its Variants
2004
This paper presents a new approach to introducing adaptive filters based on the least-mean-square (LMS) algorithm and its variants in an undergraduate course on digital signal processing. Unlike other filters currently taught to undergraduate students, these filters are nonlinear and time variant. This proposal introduces adaptive filtering in the context of a linear time-invariant system using a real problem. In this way, introducing adaptive filters using concepts already familiar to the students motivates their interest through practical application. The key point for this simplification is that the input to the filter is constant so that the adaptive filter becomes linear. Therefore, a …