Search results for "Adaptive filter"
showing 10 items of 30 documents
FPGA Implementation of an Adaptive Filter Robust to Impulsive Noise: Two Approaches
2011
Adaptive filters are used in a wide range of applications such as echo cancellation, noise cancellation, system identification, and prediction. Its hardware implementation becomes essential in many cases where real-time execution is needed. However, 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, particularly in specific hardware platforms. Field-programmable gate arrays (FPGAs) are used widely for real-time applications where timing requirements are strict. Nowadays, two main design processes can be followed for embedded system design…
Acceleration of image filtering algorithms for 3D visualization of murine lungs using dataflow engines
2015
Image filtering is one of the most common and important tasks in image processing applications. In this paper, image processing using a mean filtering algorithm combined with thresholding and binarization algorithms for the 3D visualization and analysis of murine lungs is explained. These algorithms are then mapped on the Maxler's MAX2336B Dataflow Engine (DFE) to significantly increase calculation speed. Several different DFE configurations were tested and each yielded different performance characteristics. Optimal algorithm calculation speed was up to 30 fold baseline calculation speed.
Predicting the Short-Term Exchange Rate Between United State Dollar and Czech Koruna Using Hilbert-Huang Transform and Fuzzy Logic
2017
In this paper, the combination of the Hilbert-Huang Transform, fuzzy logic and an embedding theorem is described to predict the short-term exchange rate from United States dollar to Czech Koruna. By Using the Hilbert-Huang Transform as an adaptive filter, the proposed method decreases the embedding dimension space from five (original samples) to four (de-noising samples). This dimension space provides the number of inputs to the fuzzy rule base system, which causes the number of rules, the time for training and the inference process to decrease. Experimental results indicated that this method achieves higher accuracy prediction than the direct use of original data.
Adaptive Kernel Learning for Signal Processing
2018
Adaptive filtering is a central topic in digital signal processing (DSP). By applying linear adaptive filtering principles in the kernel feature space, powerful nonlinear adaptive filtering algorithms can be obtained. This chapter introduces the wide topic of adaptive signal processing, and explores the emerging field of kernel adaptive filtering (KAF). In many signal processing applications, the problem of signal estimation is addressed. Probabilistic models have proven to be very useful in this context. The chapter discusses two families of kernel adaptive filters, namely kernel least mean squares (KLMS) and kernel recursive least‐squares (KRLS) algorithms. In order to design a practical …
Stability Analysis of a Linear Parameter Varying Adaptive Output Feedback Control System
2021
Abstract Output feedback control systems often require an adaptive filter for properly shaping the loop transfer function, as certain system plant parameters may be uncertain or varying. This renders the overall closed loop to a linear parameter varying (LPV) system, for which the stability analysis is challenging due to non-trivial dynamics of the adaptation law. This paper develops a stability analysis technique of a feedback controlled oscillatory system. A polytopic overapproximation of the parameter set together with the feasibility of certain LMIs guarantees asymptotic stability of the closed loop. The varying filter parameter is only required to be lower and upper bounded, where the …
P and R Wave Detection in Complete Congenital Atrioventricular Block
2009
Complete atrioventricular block (type III AVB) is characterized by an absence of P wave transmission to ventricles. This implies that QRS complexes are generated in an autonomous way and are not coordinated with P waves. This work introduces a new algorithm for the detection of P waves for this type of pathology using non-invasive electrocardiographic surface leads. The proposed algorithm is divided into three stages. In the first stage, the R waves located by a QRS detector are used to generate the RR series and time references for the other stages of the algorithm. In the second stage, the ventricular activity (QT segment) is removed by using an adaptive filter that obtains an averaged pa…
Real-time people counting system using a single video camera
2008
This is the copy of journal's version originally published in Proc. SPIE 6811. Reprinted with permission of SPIE: http://spie.org/x10.xml?WT.svl=tn7 There is growing interest in video-based solutions for people monitoring and counting in business and security applications. Compared to classic sensor-based solutions the video-based ones allow for more versatile functionalities, improved performance with lower costs. In this paper, we propose a real-time system for people counting based on single low-end non-calibrated video camera. The two main challenges addressed in this paper are: robust estimation of the scene background and the number of real persons in merge-split scenarios. The latter…
Echo cancellation system for iso-frequency repeaters : contribution to the development of a new generation digital repeater
2014
On-frequency repeaters are a cost-effective solution to extend coverage and enhance wireless communications, especially in shadow areas. However, coupling between the receiving antenna and the transmitting antenna, called radio frequency echo, increases modulation errors and creates oscillations in the system when the echo power is high. According to the communication standards, extremely weak echoes decrease the transmission rate, while strong echoes damage electroni ccircuits because of power peaks. This thesis aims at characterizing the echo phenomenon under different modulations, and proposing an optimized solution directly integrated to industry. We have turned to digital solutions esp…
Sensorless Control of PMSM Fractional Horsepower Drives by Signal Injection and Neural Adaptive-Band Filtering
2012
This paper presents a sensorless technique for permanent-magnet synchronous motors (PMSMs) based on high-frequency pulsating voltage injection. Starting from a speed estimation scheme well known in the literature, this paper proposes the adoption of a neural network (NN) based adaptive variable-band filter instead of a fixed-bandwidth filter, needed for catching the speed information from the sidebands of the stator current. The proposed NN filter is based on a linear NN adaptive linear neuron (ADALINE), trained with a classic least mean squares (LMS) algorithm, and is twice adaptive. From one side, it is adaptive in the sense that its weights are adapted online recursively. From another si…
Descriptor-type Robust Kalman Filter and Neural Adaptive Speed Estimation Scheme for Sensorless Control of Induction Motor Drive Systems
2012
Abstract This paper deals with robust estimation of speed and rotor flux for sensorless control of motion control systems which use induction motors as actuators. Due to the observability lack of five and six order Extended Kalman Filters, speed is here estimated by means of a Total Least Square algorithm with Neural Adaptive mechanism. This allows the use of a fourth-order Kalman Filter for estimating rotor flux and to filter stator currents. To cope with motor-load parameter variations, a descriptor-type robust Kalman Filter is designed taking explicitly into account these variations. The descriptor-type structure allows direct translation of parameter variations into variations of the co…