Quantization is a process that maps a continous or discrete set of values into approximations that belong to a smaller set. Quantization is a lossy: some information about the original data is lost in the process. The key to a successful quantization is therefore the selection of an error criterion – such as entropy and signal-to-noise ratio – and the development of optimal quantizers for this criterion.

Quantization

Several results describing the behavior of quantization noise in a unified and simplified manner are discussed. Exact formulas for quantizer noise spectra are developed. They are applied to a variety of systems and inputs, including scalar quantization (PCM), dithered PCM, sigma-delta modulation, dithered sigma-delta modulation, two-stage sigma-delta modulation, and second-order sigma-delta modulation. >

Quantization noise spectra

A lattice structure and an algorithm are presented for the design of two-channel QMF (quadrature mirror filter) banks, satisfying a sufficient condition for perfect reconstruction. The structure inherently has the perfect-reconstruction property, while the algorithm ensures a good stopband attenuation for each of the analysis filters. Implementations of such lattice structures are robust in the sense that the perfect-reconstruction property is preserved in spite of coefficient quantization. The lattice structure has the hierarchical property that a higher order perfect-reconstruction QMF bank can be obtained from a lower order perfect-reconstruction QMF bank, simply by adding more lattice sections. Several numerical examples are provided in the form of design tables. >

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Lattice structures for optimal design and robust implementation of two-channel perfect-reconstruction QMF banks

Implementation of digital controllers—a survey

The use of the delta operator in the realizations of digital filters has recently gained interest due to its good finite-word-length performance under fast sampling. We studied efficient direct form structures, and show that only some of them can be used in delta configurations, while others are evidently unstable. In this paper, we focus on the roundoff noise analysis. Of all the direct-form structures, the direct form II transposed (DFIIt) delta structure has the lowest quantization noise level at its output. This structure outperforms both the conventional direct-form (delay) structures, as well as the state-space structures for narrow-band low-pass filters with respect to output roundoff noise. Excellent roundoff noise performance is achieved at the cost of only a minor additional implementation complexity when compared with the corresponding delay realization. Complexity of a signal processor implementation of the DFIIt delta structure, which was found to be the most suitable delta structure for signal processors, is compared with those of the direct form and state-space delay structures. In addition, some hardware implementation aspects are discussed, including the minimization of the internal word length.

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Delta operator realizations of direct-form IIR filters

Roundoff error after fixed-point multiplication is commonly modeled as uniformly distributed white noise that is uncorrelated with the signal. This paper presents a statistical analysis of fixed-point roundoff error that identifies the conditions under which this model is valid, and examines the statistical behavior of roundoff error when these conditions are not satisfied. The results show that if the multiplier coefficient is expressed as a = N/M, where M is a positive integral power of two and N is an odd integer, then the errors generated by roundoff after multiplication can generally be modeled as uniformly distributed, white, and uncorrelated with the signal, if the signal has sufficiently wide bandwidth and has a dynamic range that extends over approximately M quantum steps. For narrow-band low-level signals, the roundoff error statistics can differ significantly from the uniform, white, uncorrelated model. In addition, these results show that statistical behavior of roundoff error can differ significantly from that of the quantization error that is generated when a continuous random variable is quantized.

Boi Tran

Papers

On the statistics of fixed-point roundoff error