Realization issues of block floating-point (BFP) filters such as complexity, roundoff noise, and absence of limit cycles are analyzed. Several new results are established. Under certain conditions, BFP filters perform better than fixed-point filters at the expense of a slight increase in complexity; convex programming can be used to minimize the roundoff noise; limit cycles will not be present if the underlying fixed-point system is free of quantization limit cycles. It is shown that BFP arithmetic can be efficiently combined with block implementations to further improve the roundoff noise and stability of the implementation and reduce the complexity of processing BFP data.
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