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Related Concept Videos

Complex Zeros01:29

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Complex zeros are the solutions to polynomial equations that include imaginary numbers, specifically, numbers of the form a + bi, where a and b are real numbers and i is the imaginary unit defined by i2=-1. These zeros satisfy the equation P(x) = 0, where P(x) is a polynomial with real or complex coefficients. Since the complex number system includes all real numbers, it provides a complete framework for analyzing all possible roots of a polynomial.Every polynomial of degree n≥1 can be...
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The real number system cannot represent the square root of a negative number, which restricts solutions for certain equations, such as quadratics with negative discriminants. To address this, the complex number system was developed, introducing the imaginary unit i, where i = √(-1). This extension allows for the representation of all roots, including those involving negative radicands.A complex number is written in the form x + yi, where x and y are real numbers. Here, x represents the...
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The concept of real numbers includes all the values that can be represented on a continuous number line. The system began with basic counting values used for enumeration. It later expanded to include values that represent the absence of quantity and opposites of the counting values. When situations required expressing parts of a whole or dividing quantities evenly, values capable of representing such proportions were developed. When written using decimal notation, these values can end or repeat...
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Integrals involving non-rational functions are often difficult to evaluate using standard techniques, especially when radicals appear in the integrand. Rationalizing substitution provides a systematic method for simplifying such integrals by converting them into rational forms that are easier to handle.Consider a rod whose linear mass density depends on a constant linear density, a characteristic length, and the distance from the left end of the rod. Determining the total mass requires...
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Real Zeros of Polynomials

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Polynomials are algebraic expressions of terms with variables raised to non-negative integer powers. A central aspect of analyzing polynomial functions is determining their real zeros—values of the variable for which the polynomial evaluates to zero. These values represent the x-intercepts of the polynomial’s graph.The Rational Zeros Theorem lists possible rational solutions for a polynomial equation with integer coefficients. If f(x)=anxn+....+a0​, then every rational zero is...
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Rational expressions are algebraic fractions in which both the numerator and the denominator are polynomials. These expressions follow the arithmetic rules of numerical fractions but require extra care due to the presence of variables. A fundamental part of working with rational expressions is identifying values that make the expression undefined, typically those that result in division by zero or undefined radicals.Determining the DomainThe domain of a rational expression includes all real...
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Author Spotlight: Analgesic Effect of Tuina on Rat Models with Compression of the Dorsal Root Ganglion Pain
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A test data compression scheme based on irrational numbers stored coding.

Hai-feng Wu1, Yu-sheng Cheng1, Wen-fa Zhan2

  • 1School of Computer and Information, Anqing Normal University, Anqing 246011, China.

Thescientificworldjournal
|September 27, 2014
PubMed
Summary
This summary is machine-generated.

A new irrational numbers stored (INS) scheme efficiently compresses integrated circuit test data by converting it into irrational numbers. This method shows superior compression effects compared to existing coding techniques.

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Data Compression

Background:

  • The integrated circuit industry's growth is hindered by test data volume.
  • Efficient test data compression is crucial for reducing costs and improving testing processes.

Purpose of the Study:

  • To introduce a novel test data compression scheme called irrational numbers stored (INS).
  • To evaluate the effectiveness of the INS scheme in compressing test data for integrated circuits.

Main Methods:

  • Test data is converted into floating-point numbers.
  • Floating-point numbers are precisely converted and stored as irrational numbers.
  • An algorithm for the precise conversion of floating-point to irrational numbers is detailed.

Main Results:

  • The irrational numbers stored (INS) scheme demonstrates significant test data compression.
  • Experimental results on ISCAS 89 benchmarks show superior compression compared to FDR, AARLC, INDC, FAVLC, and VRL.

Conclusions:

  • The irrational numbers stored (INS) scheme offers an effective solution for test data compression.
  • This approach can potentially alleviate limitations on integrated circuit development caused by large test data.