Responsible for this page: Lars Wanhammar , firstname.lastname@example.org
Page last update: 2008-05-08
Digital FBs have traditionally been designed in such a manner that the analysis FB and synthesis FB have the same arithmetic complexity. The objective function to minimize in these FBs is the overall complexity. However, in applications where it is important to minimize the complexity of either the analysis or the synthesis parts, the traditional FBs are not suitable. One such example is communication systems consisting of a stationary unit and a mobile unit where it is crucial to minimize the power consumption in the mobile unit whereas one can afford a somewhat higher power consumption in the stationary unit. Another example is mixed discrete-time and digital FBs for analog-to-digital conversion where the analysis filters are discrete-time filters such as SC-filters. In this case it is essential to minimize the complexity of the SC-filters since these are much more difficult to implement with a high accuracy compared to digital filters. We refer to FBs with different complexities in the analysis and synthesis parts as asymmetric FBs.
Further, the attention has traditionally to a large extent been paid to the problem of designing perfect reconstruction (PR) FBs for which the output is simply a shifted (delayed) version of the input. However, in practice FBs are most often used in applications where small errors (like quantization errors etc.) are allowed. Hence, it is rarely necessary to use PR FBs. Imposing PR on a FB is therefore an unnecessarily severe restriction which may lead to a higher arithmetic complexity than is actually required to meet the specification at hand. To reduce the complexity and power consumption one should therefore instead consider so called near-PR FBs which approximate PR.
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