Search results for " signal processing"
showing 10 items of 208 documents
Transputer-based parallel system for acquisition and on-line analysis of single-fiber electromyographic signals.
1992
Abstract We describe a transputer-based system suitable for accurate measurements of single-fiber electromyographic jitter. It consists of a conventional electromyograph, a home-made interface and a commercially available transputer-based board installed within a PC/AT compatible. Taking advantage of the concurrent operation of two transputer modules, the system features simultaneous data acquisition and statistical signal processing: while data are acquired and analyzed, a real-time visualization of the signal latency and its variability is provided. In the present configuration, the system can acquire and analyze up to 40,000 consecutive action potentials, which can be grouped into up to …
Periodic time-domain modulation for the electrically tunable control of optical pulse train envelope and repetition rate multiplication
2012
An electrically tunable system for the control of optical pulse sequences is proposed and demonstrated. It is based on the use of an electrooptic modulator for periodic phase modulation followed by a dispersive device to obtain the temporal Talbot effect. The proposed configuration allows for repetition rate multiplication with different multiplication factors and with the simultaneous control of the pulse train envelope by simply changing the electrical signal driving the modulator. Simulated and experimental results for an input optical pulse train of 10 GHz are shown for different multiplication factors and envelope shapes. © 2006 IEEE.
Signal processing and frequency-dependent associative memory based on nanoswitches
2008
A signal processing concept based on nanoscale switches whose conductance can be tuned by an external stimulus between two (ON and OFF) states is proposed and analyzed theoretically. The building block of the system is formed by a metal nanoparticle linked to two electrodes by an organic ligand and a molecular switch. When we apply an alternating potential to the system of the same frequency as the periodic variation between the ON and OFF states induced on the switch, the net charge delivered by the system exhibits a sharp resonance. This resonance can be used to process an external signal by selectively extracting the weight of the different harmonics. In addition, a frequency-dependent a…
Introduction to Digital Signal Processing
2018
Signal processing deals with the representation, transformation, and manipulation of signals and the information they contain. Typical examples include extracting the pure signals from a mixture observation (a field commonly known as deconvolution) or particular signal (frequency) components from noisy observations (generally known as filtering). This chapter outlines the basics of signal processing and then introduces the more advanced concepts of time‐frequency and time‐scale representations, as well as emerging fields of compressed sensing and multidimensional signal processing. When moving to multidimensional signal processing, a modern approach is taken from the point of view of statis…
Observer-based finite-time fuzzy H∞ control for discrete-time systems with stochastic jumps and time-delays
2014
This paper is concerned with the problem of observer-based finite-time H ∞ control for a family of discrete-time Markovian jump nonlinear systems with time-delays represented by Takagi-Sugeno (T-S) model. The main contribution of this paper is to design an observer-based finite-time H ∞ controller such that the resulting closed-loop system is stochastic finite-time bounded and satisfies a prescribed H ∞ disturbance attenuation level over the given finite-time interval. Sufficient criteria on stochastic finite-time H ∞ stabilization via observer-based fuzzy state feedback are presented for the solvability of the problem, which can be tackled by a feasibility problem in terms of linear matrix…
Arbitrary Phase Access for Stable Fiber Interferometers
2021
Well-controlled yet practical systems that give access to interference effects are critical for established and new functionalities in ultrafast signal processing, quantum photonics, optical coherence characterization, etc. Optical fiber systems constitute a central platform for such technologies. However, harnessing optical interference in a versatile and stable manner remains technologically costly and challenging. Here, degrees of freedom native to optical fibers, i.e., polarization and frequency, are used to demonstrate an easily deployable technique for the retrieval and stabilization of the relative phase in fiber interferometric systems. The scheme gives access (without intricate dev…
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 …
From Signal Processing to Machine Learning
2018
This chapter reviews the main landmarks of signal processing in the 20th century from the perspective of algorithmic developments. It focuses on cross‐fertilization with the field of statistical (machine) learning in the last decades. In the 21st century, model and data assumptions as well as algorithmic constraints are no longer valid, and the field of machine‐learning signal processing has erupted, with many successful stories to tell. The chapter also focuses on digital signal processing (DSP), which deals with the analysis of digitized and discrete sampled signals. Machine learning is a branch of computer science and artificial intelligence that enables computers to learn from data. Mac…