Add to ORKGThe statistical theory of quantization makes possible to design measurement procedures with quantized data. If carefully interpreted, this theory provides formulae to estimate bias and variance of quantized measurements and may show the means to reduce effectively the errors of quantized measurements. Limitations of the applicability of the theory are discussed too
System identification based on quantized observations requires either approximations of the quantiza...
Quantisation of a signal or data source refers to the division or classification of that source into...
In this paper, a noise analysis of a modulated quantizer is performed. If input signals are oversamp...
Computer quantization is important to consider in digital signal processing because it limits the ac...
We consider two different problems in quantization theory. During the first part we discuss the so c...
AbstractWe discuss the trade-off between sampling and quantization in signal processing for the purp...
In this thesis we study a scalar uniform and non-uniform quantization of random processes (or signal...
Quantization of a continuous-value signal into a discrete form (or discretization of amplitude) is a...
Due to the rapidly increasing need for methods of data compression, quantization has become a flouri...
Statistical description of quantization process is common in the theory of quantization. For the cas...
In this paper, we continue a topic of modeling measuring processes by perceiving them as a kind of s...
The linear reconstruction phase of analog-to-digital (A/D) conversion in signal processing is analyz...
Typically an analog signal from a space system is sampled, quantized by Analog-to-Digital (A/D) conv...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
This paper examines the correlation properties of quantization noise. The quantization noise energy ...
System identification based on quantized observations requires either approximations of the quantiza...
Quantisation of a signal or data source refers to the division or classification of that source into...
In this paper, a noise analysis of a modulated quantizer is performed. If input signals are oversamp...
Computer quantization is important to consider in digital signal processing because it limits the ac...
We consider two different problems in quantization theory. During the first part we discuss the so c...
AbstractWe discuss the trade-off between sampling and quantization in signal processing for the purp...
In this thesis we study a scalar uniform and non-uniform quantization of random processes (or signal...
Quantization of a continuous-value signal into a discrete form (or discretization of amplitude) is a...
Due to the rapidly increasing need for methods of data compression, quantization has become a flouri...
Statistical description of quantization process is common in the theory of quantization. For the cas...
In this paper, we continue a topic of modeling measuring processes by perceiving them as a kind of s...
The linear reconstruction phase of analog-to-digital (A/D) conversion in signal processing is analyz...
Typically an analog signal from a space system is sampled, quantized by Analog-to-Digital (A/D) conv...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer...
This paper examines the correlation properties of quantization noise. The quantization noise energy ...
System identification based on quantized observations requires either approximations of the quantiza...
Quantisation of a signal or data source refers to the division or classification of that source into...
In this paper, a noise analysis of a modulated quantizer is performed. If input signals are oversamp...