SRT radix-2 dividers with (5,4) redundant representation of partial remainder

Author(s):  
Alexandru Amaricai ◽  
Oana Boncalo
2017 ◽  
Vol 26 (06) ◽  
pp. 1750097
Author(s):  
Alexandru Amaricai ◽  
Ovidiu Sicoe ◽  
Oana Boncalo

Most digit-recurrence algorithms for division, such as the Sweeney–Robertson–Tocher (SRT) algorithm, have been used in order to take advantage of the redundant representations of the partial remainder. This way, full carry propagate additions are avoided, obtaining significant latency improvements. Furthermore, the delay corresponding to one division iteration is independent of the size of the operands. The most frequent redundant form for the partial remainders is the carry-save (CS) representation, which uses 2 bits of representation (carry and sum bits) for each bit of the partial remainder. This paper proposes radix-4 SRT dividers which use (3, 2) redundancy (3 bits of representation for 2 bits of the partial remainder) and (5, 4) redundancy (5 bits of representation for 4 bits of the partial remainder). The goal of using these representations is represented by a decreased cost due to the reduced number of sequential elements required to store the partial remainder. The proposed dividers use 2-bit carry propagate adders and 4-bit carry propagate adders to compute the new partial remainder. Thus, the full carry propagate addition is avoided, while the latency of one division iteration is independent of the operands’ size. The synthesis result for Xilinx Virtex-5 FPGA devices show that similar working frequencies are obtained for divider using the proposed redundant representation with respect to the conventional carry-save, while requiring up to 12% for (3, 2) representation and 18% for (5, 4) representation less sequential elements.


2017 ◽  
Vol 32 (3) ◽  
pp. 2142-2151 ◽  
Author(s):  
Yi Wang ◽  
Qixin Chen ◽  
Chongqing Kang ◽  
Qing Xia ◽  
Min Luo

2017 ◽  
Vol 15 (03) ◽  
pp. 333-352
Author(s):  
Yu Xia ◽  
Song Li

This paper considers the nonuniform sparse recovery of block signals in a fusion frame, which is a collection of subspaces that provides redundant representation of signal spaces. Combined with specific fusion frame, the sensing mechanism selects block-vector-valued measurements independently at random from a probability distribution [Formula: see text]. If the probability distribution [Formula: see text] obeys a simple incoherence property and an isotropy property, we can faithfully recover approximately block sparse signals via mixed [Formula: see text]-minimization in ways similar to Compressed Sensing. The number of measurements is significantly reduced by a priori knowledge of a certain incoherence parameter [Formula: see text] associated with the angles between the fusion frame subspaces. As an example, the paper shows that an [Formula: see text]-sparse block signal can be exactly recovered from about [Formula: see text] Fourier coefficients combined with fusion frame [Formula: see text], where [Formula: see text].


Author(s):  
OFER AMRANI ◽  
AMIR AVERBUCH ◽  
TAMIR COHEN ◽  
VALERY A. ZHELUDEV

A new class of wavelet-type frames in signal space that uses (anti)symmetric waveforms is presented. The construction employs interpolatory filters with rational transfer functions. These filters have linear phase. They are amenable either to fast cascading or parallel recursive implementation. Robust error recovery algorithms are developed by utilizing the redundancy inherent in frame expansions. Experimental results recover images when (as much as) 60% of the expansion coefficients are either lost or corrupted. The proposed approach inflates the size of the image through framelet expansion and multilevel decomposition thus providing redundant representation of the image. Finally, the frame-based error recovery algorithm is compared with a classical coding approach.


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