<p>In this paper, we present a weak version (called weak EC inverse) of the recently defined EC inverse of a complex square matrix. More precisely, for any <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq1.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="49" /> </InlineMediaObject> <EquationSource Format="TEX">\(m\times n\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>m</mi> <mo>×</mo> <mi>n</mi> </mrow> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="49" /> </InlineMediaObject> <EquationSource Format="TEX">\(n\times m\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mo>×</mo> <mi>m</mi> </mrow> </math></EquationSource> </InlineEquation> complex matrices <i>A</i> and <i>X</i>, respectively, it is proved that there exists a unique complex matrix <i>Y</i> of size <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq2.gif" Format="GIF" Height="13" Rendition="HTML" Resolution="72" Type="Linedraw" Width="49" /> </InlineMediaObject> <EquationSource Format="TEX">\(n\times m\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>n</mi> <mo>×</mo> <mi>m</mi> </mrow> </math></EquationSource> </InlineEquation> that satisfies <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq4.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="78" /> </InlineMediaObject> <EquationSource Format="TEX">\(AYA=A\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>A</mi> <mi>Y</mi> <mi>A</mi> <mo>=</mo> <mi>A</mi> </mrow> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq5.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="76" /> </InlineMediaObject> <EquationSource Format="TEX">\(YAY=Y\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>Y</mi> <mi>A</mi> <mi>Y</mi> <mo>=</mo> <mi>Y</mi> </mrow> </math></EquationSource> </InlineEquation>, <InlineEquation ID="IEq6"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq6.gif" Format="GIF" Height="19" Rendition="HTML" Resolution="72" Type="Linedraw" Width="94" /> </InlineMediaObject> <EquationSource Format="TEX">\((AY)^*=AY\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mrow> <mo stretchy="false">(</mo> <mi>A</mi> <mi>Y</mi> <mo stretchy="false">)</mo> </mrow> <mo>∗</mo> </msup> <mo>=</mo> <mi>A</mi> <mi>Y</mi> </mrow> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq7"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq7.gif" Format="GIF" Height="18" Rendition="HTML" Resolution="72" Type="Linedraw" Width="212" /> </InlineMediaObject> <EquationSource Format="TEX">\(YA=A^\dag A+XA-A^\dag AXA\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>Y</mi> <mi>A</mi> <mo>=</mo> <msup> <mi>A</mi> <mo>†</mo> </msup> <mi>A</mi> <mo>+</mo> <mi>X</mi> <mi>A</mi> <mo>-</mo> <msup> <mi>A</mi> <mo>†</mo> </msup> <mi>A</mi> <mi>X</mi> <mi>A</mi> </mrow> </math></EquationSource> </InlineEquation>. When <InlineEquation ID="IEq8"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="43037_2025_432_Article_IEq8.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="59" /> </InlineMediaObject> <EquationSource Format="TEX">\(X=A^\dag \)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <mi>X</mi> <mo>=</mo> <msup> <mi>A</mi> <mo>†</mo> </msup> </mrow> </math></EquationSource> </InlineEquation>, such a matrix <i>Y</i> reduces to the Moore-Penrose inverse. When <i>A</i> is a square complex matrix and <i>X</i> is a minimal rank weak Drazin inverse of <i>A</i>, different properties and representations of the weak EC inverse are developed. In particular, when <i>X</i> is the Drazin inverse, a new inverse (called spectral core inverse) with some spectral properties is presented as a special case of the weak EC inverse, which is expressed as sum and difference of the Moore-Penrose, DMP and CMP inverses. Also, applications of the weak EC inverse in solving minimizations problems and linear equations are obtained.</p>

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Weak extended core inverse

  • D. Mosić,
  • D. E. Ferreyra

摘要

In this paper, we present a weak version (called weak EC inverse) of the recently defined EC inverse of a complex square matrix. More precisely, for any \(m\times n\) m × n and \(n\times m\) n × m complex matrices A and X, respectively, it is proved that there exists a unique complex matrix Y of size \(n\times m\) n × m that satisfies \(AYA=A\) A Y A = A , \(YAY=Y\) Y A Y = Y , \((AY)^*=AY\) ( A Y ) = A Y and \(YA=A^\dag A+XA-A^\dag AXA\) Y A = A A + X A - A A X A . When \(X=A^\dag \) X = A , such a matrix Y reduces to the Moore-Penrose inverse. When A is a square complex matrix and X is a minimal rank weak Drazin inverse of A, different properties and representations of the weak EC inverse are developed. In particular, when X is the Drazin inverse, a new inverse (called spectral core inverse) with some spectral properties is presented as a special case of the weak EC inverse, which is expressed as sum and difference of the Moore-Penrose, DMP and CMP inverses. Also, applications of the weak EC inverse in solving minimizations problems and linear equations are obtained.