Quantization Dimension Research Articles

Quantization dimension for conformal iterated function systems

The quantization dimension function is determined for a certain class of probability measures generated bya finite conformal iterated function system satisfying the strong open set condition.

The quantization dimension of distributions

We show that the asymptotic behaviour of the quantization error allows the definition of dimensions for probability distributions, the upper and the lower quantization dimension. These concepts fit into standard geometric measure theory, as the upper quantization dimension is always between the packing and the upper box-counting dimension, whereas the lower quantization dimension is between the Hausdorff and the lower box-counting dimension.

Spectral Characteristics of Linewidth Enhancement Factor α of Multidimensional Quantum Wells

We calculated spectral characteristics of the linewidth enhancement factor α for multidimensional quantum-well lasers. By increasing the quantization dimension, the wavelength dependence of α becomes stronger and its value around the maximum gain becomes smaller. For a quantum box, α is almost zero at the gain peak, and becomes negative at a shorter wavelength. The negative α yields the possibility of long-distance high-capacity optical fiber communication.

Asymptotic quantization error of continuous signals and the quantization dimension

Extensions of the limiting qnanfizafion error formula of Bennet are proved. These are of the form <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D_{s,k}(N,F)=N^{-\beta}B</tex> , where <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">N</tex> is the number of output levels, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">D_{s,k}(N,F)</tex> is the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">s</tex> th moment of the metric distance between quantizer input and output, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">\beta,B&gt;0,k=s/\beta</tex> is the signal space dimension, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</tex> is the signal distribution. If a suitably well-behaved <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</tex> -dimensional signal density <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f(x)</tex> exists, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">B=b_{s,k}[\int f^{\rho}(x)dx]^{1/ \rho},\rho=k/(s+k)</tex> , and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">b_{s,k}</tex> does not depend on <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f</tex> . For <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k=1,s=2</tex> this reduces to Bennett's formula. If <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">F</tex> is the Cantor distribution on <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[0,1],0&lt;k=s/ \beta=\log 2/ \log 3&lt;1</tex> and this <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">k</tex> equals the fractal dimension of the Cantor set <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[12,13]</tex> . Random quantization, optimal quantization in the presence of an output information constraint, and quantization noise in high dimensional spaces are also investigated.