121,024 research outputs found
Latency Optimized Asynchronous Early Output Ripple Carry Adder based on Delay-Insensitive Dual-Rail Data Encoding
Asynchronous circuits employing delay-insensitive codes for data
representation i.e. encoding and following a 4-phase return-to-zero protocol
for handshaking are generally robust. Depending upon whether a single
delay-insensitive code or multiple delay-insensitive code(s) are used for data
encoding, the encoding scheme is called homogeneous or heterogeneous
delay-insensitive data encoding. This article proposes a new latency optimized
early output asynchronous ripple carry adder (RCA) that utilizes single-bit
asynchronous full adders (SAFAs) and dual-bit asynchronous full adders (DAFAs)
which incorporate redundant logic and are based on the delay-insensitive
dual-rail code i.e. homogeneous data encoding, and follow a 4-phase
return-to-zero handshaking. Amongst various RCA, carry lookahead adder (CLA),
and carry select adder (CSLA) designs, which are based on homogeneous or
heterogeneous delay-insensitive data encodings which correspond to the
weak-indication or the early output timing model, the proposed early output
asynchronous RCA that incorporates SAFAs and DAFAs with redundant logic is
found to result in reduced latency for a dual-operand addition operation. In
particular, for a 32-bit asynchronous RCA, utilizing 15 stages of DAFAs and 2
stages of SAFAs leads to reduced latency. The theoretical worst-case latencies
of the different asynchronous adders were calculated by taking into account the
typical gate delays of a 32/28nm CMOS digital cell library, and a comparison is
made with their practical worst-case latencies estimated. The theoretical and
practical worst-case latencies show a close correlation....Comment: arXiv admin note: text overlap with arXiv:1704.0761
A Convex Model for Edge-Histogram Specification with Applications to Edge-preserving Smoothing
The goal of edge-histogram specification is to find an image whose edge image
has a histogram that matches a given edge-histogram as much as possible.
Mignotte has proposed a non-convex model for the problem [M. Mignotte. An
energy-based model for the image edge-histogram specification problem. IEEE
Transactions on Image Processing, 21(1):379--386, 2012]. In his work, edge
magnitudes of an input image are first modified by histogram specification to
match the given edge-histogram. Then, a non-convex model is minimized to find
an output image whose edge-histogram matches the modified edge-histogram. The
non-convexity of the model hinders the computations and the inclusion of useful
constraints such as the dynamic range constraint. In this paper, instead of
considering edge magnitudes, we directly consider the image gradients and
propose a convex model based on them. Furthermore, we include additional
constraints in our model based on different applications. The convexity of our
model allows us to compute the output image efficiently using either
Alternating Direction Method of Multipliers or Fast Iterative
Shrinkage-Thresholding Algorithm. We consider several applications in
edge-preserving smoothing including image abstraction, edge extraction, details
exaggeration, and documents scan-through removal. Numerical results are given
to illustrate that our method successfully produces decent results efficiently
- …