A note on the cubical dimension of new classes of binary trees

Kabyl, Kamal; Berrachedi, Abdelhafid; Sopena, Éric

doi:10.1007/s10587-015-0165-6

Cited by 2 publications

(7 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…symbolizes the total number of nodes in the graph . Let a hypercube be characterized as = ( , ), where is the dimension, is the set of edges, and is the set of vertices of the hypercube [16]. The cardinality of and is given in (3) and (4), respectively.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

FPGA Implementation of an Improved Reconfigurable FSMIM Architecture Using Logarithmic Barrier Function Based Gradient Descent Approach

Das

Panchanathan

2019

International Journal of Reconfigurable Computing

View full text Add to dashboard Cite

Recently, the Reconfigurable FSM has drawn the attention of the researchers for multistage signal processing applications. The optimal synthesis of Reconfigurable finite state machine with input multiplexing (Reconfigurable FSMIM) architecture is done by the iterative greedy heuristic based Hungarian algorithm (IGHA). The major problem concerning IGHA is the disintegration of a state encoding technique. This paper proposes the integration of IGHA with the state assignment using logarithmic barrier function based gradient descent approach to reduce the hardware consumption of Reconfigurable FSMIM. Experiments have been performed using MCNC FSM benchmarks which illustrate a significant area and speed improvement over other architectures during field programmable gate array (FPGA) implementation.

show abstract

Section: Methodsmentioning

confidence: 99%

“…Now, the concept of hypercube embedding is used to reduce (2). An embedding is performed from graph onto a hypercube as described earlier [16,17]. It is defined as :…”

Section: Methodsmentioning

confidence: 99%

FPGA Implementation of an Improved Reconfigurable FSMIM Architecture Using Logarithmic Barrier Function Based Gradient Descent Approach

Das

Panchanathan

2019

International Journal of Reconfigurable Computing

View full text Add to dashboard Cite

show abstract

“…Let a hypercube be characterized as ] = ( , ), where ] is the dimension, is the set of vertices of ] , and is the set of edges of ] [21]. The total number of elements present in and , are defined by (11) and (12).…”

Section: Methodsmentioning

confidence: 99%

“…The hypercube embedding is applied to minimize (10). It is executed from graph into the hypercube ] [21,22]. It is symbolized as : → .…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Gradient‐Based Interior‐Point Method to Solve the Many‐to‐Many Assignment Problems

Das

Priya

2019

Complexity

View full text Add to dashboard Cite

The many-to-many assignment problem (MMAP) is a recent topic of study in the field of combinatorial optimization. In this paper, a gradient-based interior-point method is proposed to solve MMAP. It is a deterministic method which assures an optimal solution. In this approach, the relaxation of the constraints is performed initially using the cardinality constraint detection operation. Then, the logarithmic barrier function (LBF) based gradient descent approach is executed to reach an accurate solution. Experiments have been performed to validate the practical implementation of the proposed algorithm. It also illustrates a significant improvement in convergence speed for the large MMAPs (i.e., if group size, α≥80) over state-of-the-art literature.

show abstract

A note on the cubical dimension of new classes of binary trees

Cited by 2 publications

References 14 publications

FPGA Implementation of an Improved Reconfigurable FSMIM Architecture Using Logarithmic Barrier Function Based Gradient Descent Approach

FPGA Implementation of an Improved Reconfigurable FSMIM Architecture Using Logarithmic Barrier Function Based Gradient Descent Approach

A Gradient‐Based Interior‐Point Method to Solve the Many‐to‐Many Assignment Problems

Contact Info

Product

Resources

About