adaptive algorithms offer a wide area of research in the field of digital signal processing. If the received signal is changing with time so as the noise the need for predictive algorithms to be adaptive with the chan...
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ISBN:
(纸本)9781538642542
adaptive algorithms offer a wide area of research in the field of digital signal processing. If the received signal is changing with time so as the noise the need for predictive algorithms to be adaptive with the changes becomes predominant further noise being a random signal strongly needs an adaptive approach for analysis and thus presents a wide scope for research. This paper presents a basic comparative study of various adaptive algorithms such as least mean square (LMS) algorithm, recursive least square (RLS) algorithm and other adaptive algorithms with their application in active noise cancellation. The purpose of presenting this paper is to provide an insight of the initial building blocks of an adaptive algorithm for use in development of further complex algorithms.
This paper presents a rigous conditions, without the independence assumtion on the input signal, for the first and second moment convergence of the gradient adaptive algorithms including FIR and IIR (equation error me...
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This paper studies the problem of adaptively sampling from K distributions (arms) in order to identify the largest gap between any two adjacent means. We call this the MaxGap-bandit problem. This problem arises natura...
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This paper studies the problem of adaptively sampling from K distributions (arms) in order to identify the largest gap between any two adjacent means. We call this the MaxGap-bandit problem. This problem arises naturally in approximate ranking, noisy sorting, outlier detection, and top-arm identification in bandits. The key novelty of the MaxGap bandit problem is that it aims to adaptively determine the natural partitioning of the distributions into a subset with larger means and a subset with smaller means, where the split is determined by the largest gap rather than a pre-specified rank or threshold. Estimating an arm's gap requires sampling its neighboring arms in addition to itself, and this dependence results in a novel hardness parameter that characterizes the sample complexity of the problem. We propose elimination and UCB-style algorithms and show that they are minimax optimal. Our experiments show that the UCB-style algorithms require 6-8x fewer samples than non-adaptive sampling to achieve the same error.
The "Propose-Test-Release" (PTR) framework [Dwork and Lei, 2009] is a classic recipe for designing differentially private (DP) algorithms that are data-adaptive, i.e. those that add less noise when the input...
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The "Propose-Test-Release" (PTR) framework [Dwork and Lei, 2009] is a classic recipe for designing differentially private (DP) algorithms that are data-adaptive, i.e. those that add less noise when the input dataset is "nice". We extend PTR to a more general setting by privately testing data-dependent privacy losses rather than local sensitivity, hence making it applicable beyond the standard noise-adding mechanisms, e.g. to queries with unbounded or undefined sensitivity. We demonstrate the versatility of generalized PTR using private linear regression as a case study. Additionally, we apply our algorithm to solve an open problem from "Private Aggregation of Teacher Ensembles (PATE)" [Papernot et al., 2017, 2018] - privately releasing the entire model with a delicate data-dependent analysis.
Agent-oriented system seems to be the attractive tool useful for numerous domains of applications. It gives the ability to integrate results of different domains of computer science and constitutes the powerful tool f...
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Agent-oriented system seems to be the attractive tool useful for numerous domains of applications. It gives the ability to integrate results of different domains of computer science and constitutes the powerful tool for solving various problems. The new approach to the simulation particularly in bio-computing and adaptive systems is possible to be developed mainly due to the results of the interactions among intelligent agents in complex adaptive systems. The modern agent-oriented paradigm allows understand the adaptive (e. g. finite element / finite difference) algorithms as a collection of interacting agents making local decision about refinements. This workshop focuses on the various applications of agent-oriented and adaptive systems and the roles of interactions of intelligent agents to build intelligent systems for miscellaneous, interesting applications. (C) 2010 Published by Elsevier Ltd.
This paper shows through theory and simulation the superiority of model-based adaptive algorithms relative to observation-only-based adaptive algorithms, such as LMS and RLS, when applied to tracking time-varying chan...
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ISBN:
(纸本)9780780393912
This paper shows through theory and simulation the superiority of model-based adaptive algorithms relative to observation-only-based adaptive algorithms, such as LMS and RLS, when applied to tracking time-varying channels. The model-based formulation reveals RLS as a degenerate algorithm which does not explicitly recognize the time-varying nature of the channel and consequently is ill-suited to tracking in non-stationary environments. Simulation results for MSE performance of the various adaptive algorithms applied to adaptive MMSE multiuser receiver corroborate the theoretical analysis.
This paper analyzes excursions of adaptive algorithms. The distribution of the number of excursions in n units of time is approximated by a Poisson distribution. The mean and distribution of the time of the occurrence...
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ISBN:
(纸本)0780324536
This paper analyzes excursions of adaptive algorithms. The distribution of the number of excursions in n units of time is approximated by a Poisson distribution. The mean and distribution of the time of the occurrence of the first excursion are approximated by those of an exponential distribution. Expressions for the error in the approximations are derived. The approximations are shown to hold asymptotically as the excursion defining set converges to the empty set and as the algorithm's step size μ converges to zero. The validity of the approximations is tested on a variety of examples.
This work presents set-membership adaptive algorithms based on time-varying error bounds. The important issue of error bound specification is addressed in a new framework that takes into account parameter estimation d...
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ISBN:
(纸本)9780780393899
This work presents set-membership adaptive algorithms based on time-varying error bounds. The important issue of error bound specification is addressed in a new framework that takes into account parameter estimation dependency, multi-access (MAI) and inter-symbol interference (ISI) for DS-CDMA communications. An algorithm for tracking and estimating the interference power is presented and incorporated into the time-varying error bound. Computer simulations show that the new algorithms are capable of outperforming previously reported techniques with a smaller number of parameter updates and a reduced risk of overbounding or underbounding.
This paper presents a study on the performance of adaptive control algorithms designed to reduce the vibration of mechanical systems excited by a harmonic disturbance. The mechanical system consists of a mass suspende...
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This paper presents a study on the performance of adaptive control algorithms designed to reduce the vibration of mechanical systems excited by a harmonic disturbance. The mechanical system consists of a mass suspended on a spring and a damper. The system is equipped with a force actuator in parallel with the suspension. The control signal driving the actuator is generated by adjusting the amplitude and phase of a sinusoidal reference signal at the same frequency as the excitation. An adaptive feedforward control algorithm is used to adapt the amplitude and phase of the control signal, to minimise the mean square velocity of the mass. Two adaptation strategies are considered in which the control signal is either updated after each period of the oscillation or at every time sample. The first strategy is traditionally used in vibration control in helicopters for example;the second strategy is normally referred to as the filtered-x least mean square algorithm and is often used to control engine noise in cars. The two adaptation strategies are compared through a parametric study, which investigates the influence of the properties of both the mechanical system and the control system on the convergence speed of the two algorithms.
This paper1 establishes a general relation between the two-dimensional Least Mean Square (2-D LMS) algorithm and 2-D discrete orthogonal transforms. It is shown that the 2-D LMS algorithm can be used to compute the fo...
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