Search results for "Adaptive filter"
showing 10 items of 30 documents
Hardware implementation of a robust adaptive filter: Two approaches based in High-Level Synthesis design tools
2009
Abstract Adaptive filters are used in a wide range of applications. Impulsive noise affects the proper operation of the filter and the adaptation process. This noise is one of the most damaging types of signal distortion, not always considered when implementing algorithms. Field Programmable Gate Array (FPGA) are widely used for applications where timing requirements are strict. Nowadays, two main design processes can be followed, namely, Hardware Description Language (HDL) and a High Level Synthesis (HLS) design tool for embedded system design. This paper describes the FPGA implementation of an adaptive filter robust to impulsive noise using two approaches based in HLS and the implementati…
Bearing fault detection for drivetrains using adaptive filters based wavelet transform
2017
Predicting a localized defect on a rolling bearing during the degradation process before a complete failure is crucial to prevent system failures, unscheduled downtimes and substantial loss of productivity. During this process, impulses associated with the fault are weak, nonstationary or time-frequency varying, and contaminated by noises, which render the problem of extracting these impulses very difficult. This work investigates the effectiveness of common signal processing techniques on predicting incipient faults, e.g. Fast Fourier transform, Short-Time Fourier transform, Wavelet transform. It was found that an adaptive filter is required to enhance and reconstruct the signals during th…
Parsimonious adaptive rejection sampling
2017
Monte Carlo (MC) methods have become very popular in signal processing during the past decades. The adaptive rejection sampling (ARS) algorithms are well-known MC technique which draw efficiently independent samples from univariate target densities. The ARS schemes yield a sequence of proposal functions that converge toward the target, so that the probability of accepting a sample approaches one. However, sampling from the proposal pdf becomes more computationally demanding each time it is updated. We propose the Parsimonious Adaptive Rejection Sampling (PARS) method, where an efficient trade-off between acceptance rate and proposal complexity is obtained. Thus, the resulting algorithm is f…
Foetal ECG recovery using dynamic neural networks
2002
Non-invasive electrocardiography has proven to be a very interesting method for obtaining information about the foetus state and thus to assure its well-being during pregnancy. One of the main applications in this field is foetal electrocardiogram (ECG) recovery by means of automatic methods. Evident problems found in the literature are the limited number of available registers, the lack of performance indicators, and the limited use of non-linear adaptive methods. In order to circumvent these problems, we first introduce the generation of synthetic registers and discuss the influence of different kinds of noise to the modelling. Second, a method which is based on numerical (correlation coe…
Implementation of a new adaptive algorithm using fuzzy cost function and robust to impulsive noise
2012
Adaptive filters are used in a wide range of applications such as noise cancellation, system identification, and prediction. One of the main problems for theses filters is the impulsive noise as it generates algorithm unstability. This work shows the development, simulation and hardware implementation of a new algorithm robust to impulsive noise. Hardware implementation becomes essential in many cases where a real time execution, reduced size, or low power system is needed. An efficient hardware architecture is proposed and different optimizations for size and speed are developed: no need for control state machine, reduced computation requirements due to simplifications, etc. Furthermore, t…
Explicit Recursive and Adaptive Filtering in Reproducing Kernel Hilbert Spaces
2014
This brief presents a methodology to develop recursive filters in reproducing kernel Hilbert spaces. Unlike previous approaches that exploit the kernel trick on filtered and then mapped samples, we explicitly define the model recursivity in the Hilbert space. For that, we exploit some properties of functional analysis and recursive computation of dot products without the need of preimaging or a training dataset. We illustrate the feasibility of the methodology in the particular case of the $\gamma$ -filter, which is an infinite impulse response filter with controlled stability and memory depth. Different algorithmic formulations emerge from the signal model. Experiments in chaotic and elect…
Flat-top ultra-wideband photonic filters based on mutual coherence function synthesis
2008
A novel all-incoherent optical circuit that allows for band-pass microwave-photonic filter design is presented and verified through numerical simulation. In contrast to conventional spectrum-sliced optical architectures that operate on the basis of a finite number of discrete taps, our proposal is based on arbitrary shaping of the spectrum of the broadband optical source in a conventional frequency encoder. This fact dramatically increases the free spectral range of the filter with respect to the conventional discrete-time optical processing. The filter transfer function is given by the mutual coherence function of the filtered source which allows, through an inverse problem, sculpting the …
DarkFocus: numerical autofocusing in digital in-line holographic microscopy using variance of computational dark-field gradient
2020
Abstract We report on a novel computational technique for automatic numerical refocusing in digital in-line holographic microscopy. It is based on the adaptive filtering of the recorded on-axis hologram to eliminate its background term and extract interference intensity-component connected with light scattered on the sample (interference fringes). Numerical propagation of such filtered hologram yields the computationally generated dark-field imaging coming from the amplitude part of the complex field. We propose a simple measure in the form of the variance of the dark-field gradient, which attains its maximum value in the focal planes for all types of objects (phase, amplitude and mixed pha…
Generalization of Canny–Deriche filter for detection of noisy exponential edge
2002
This paper presents a generalization of the Canny-Deriche filter for ramp edge detection with optimization criteria used by Canny (signal-to-noise ratio, localization, and suppression of false responses). Using techniques similar to those developed by Deriche, we derive a filter which maximizes the product of the first two criteria under the constraint of the last one. The result is an infinite length impulse response filter which leads to a stable third-order recursive implementation. Its performance shows an increase of the signal-to-noise ratio in the case of blurred and noisy images, compared to the results obtained from Deriche's filter.
Noise Filtering Using Edge-Driven Adaptive Anisotropic Diffusion
2008
This paper presents a method aimed to noise removal in MRI (Magnetic Resonance Imaging). We propose an improvement of Perona and Malik's anisotropic diffusion filter. In our schema, the diffusion equation of the filter has been modified to take into account the edges direction, This allows the filter to blur uniform areas, while it better preserves the edges. Both quantitative and qualitative evaluation is presented and the results are compared with other methods.