1974Journal of Dynamic Systems Measurement and ControlRequires access

Recent Developments in Numerical Integration

James Morton Smith

Open publisher page 16 citations

Abstract

Classical and even modern developments of numerical integration have not been directly concerned with the frequency-response of integration algorithms. The frequency-response characteristics of an integrator are usually presented only as a property of the integrator. When numerical integration is used in all digital (or hybrid) simulation, digital computer controlled systems or other discrete information systems, much care is given to selecting a numerical integration formula with well-behaved frequency-response characteristics. This paper is concerned with the development of a set of numerical integrators suited for application in information systems. These integrators are synthesized in such a way that they have well-defined frequency-response characteristics WHICH CAN BE VARIED; thus, each of these integrators can be tailored to integrate accurately and efficiently in many different applications. These methods of numerical integration have stability, accuracy, and noise-controlling parameters. Analytical and empirical methods of selecting the values of these parameters are discussed in detail.

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What this paper is about

Classical and even modern developments of numerical integration have not been directly concerned with the frequency-response of integration algorithms. The frequency-response characteristics of an integrator are usually presented only as a property of the integrator. When numerical integration is used in all digital (or hybrid) simulation, digital computer controlled systems or other discrete information systems, much care is given to selecting a numerical integration formula with well-behaved frequency-response characteristics. This paper is concerned with the development of a set of numerical integrators suited for application in information systems. These integrators are synthesized in such a way that they have well-defined frequency-response characteristics WHICH CAN BE VARIED; thus, each of these integrators can be tailored to integrate accurately and efficiently in many different applications. These methods of numerical integration have stability, accuracy, and noise-controlling parameters. Analytical and empirical methods of selecting the values of these parameters are discussed in detail.

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Available abstract

Classical and even modern developments of numerical integration have not been directly concerned with the frequency-response of integration algorithms. The frequency-response characteristics of an integrator are usually presented only as a property of the integrator. When numerical integration is used in all digital (or hybrid) simulation, digital computer controlled systems or other discrete information systems, much care is given to selecting a numerical integration formula with well-behaved frequency-response characteristics. This paper is concerned with the development of a set of numerical integrators suited for application in information systems. These integrators are synthesized in such a way that they have well-defined frequency-response characteristics WHICH CAN BE VARIED; thus, each of these integrators can be tailored to integrate accurately and efficiently in many different applications. These methods of numerical integration have stability, accuracy, and noise-controlling parameters. Analytical and empirical methods of selecting the values of these parameters are discussed in detail.

Key concepts: Integrator, Numerical integration, Computer science, Noise (video), Stability (learning theory), Frequency response, Numerical stability, Numerical analysis

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