2008 Joint 6th International IEEE Northeast Workshop on Circuits and Systems and TAISA Conference 2008
DOI: 10.1109/newcas.2008.4606354
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Optimization of the noise transfer function of Extended-Frequency-Band-Decomposition sigma-delta A/D converters

Abstract: Abstract-Frequency-Band-Decomposition (FBD) is a good candidate to increase the bandwidths of ADC converters based on sigma-delta modulators. Each modulator processes a part of the input signal band and is followed by a digital filter. In the case of large mismatches in the analog modulators, a new solution, called Extended Frequency-Band-Decomposition (EFBD) can be used. This solution allows for, for example, a four percent error in the central frequencies without significant degradation in the performance wh… Show more

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Cited by 3 publications
(3 citation statements)
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“…In order to reduce the requirement of high clock speed in some parts of the signal processing units, different parallel processing techniques have been introduced, including frequency band decomposition (FBD) [19], Hadamard transformer-based approach [20], [21], and the timeinterleaving (TI) techniques [22], [23], [24], [25].…”
Section: B Parallel Branches Based Dsmsmentioning
confidence: 99%
“…In order to reduce the requirement of high clock speed in some parts of the signal processing units, different parallel processing techniques have been introduced, including frequency band decomposition (FBD) [19], Hadamard transformer-based approach [20], [21], and the timeinterleaving (TI) techniques [22], [23], [24], [25].…”
Section: B Parallel Branches Based Dsmsmentioning
confidence: 99%
“…1) . The proposed algorithm is based on a so-called relaxation method [18]. It does not require any operations except the calculation of the output power.…”
Section: Noise Transfer Function Calibration Algorithmmentioning
confidence: 99%
“…The proposed algorithm is based on a so-called relaxation method [18]. It does not require any operations except the calculation of the output power.…”
Section: Noise Transfer Function Calibration Algorithmmentioning
confidence: 99%