Apparatus and method of low complexity optimization solver for path smoothing with constraint variation
AssigneeSamsung Electronics Co., Ltd.
InventorsBinnan Zhuang, Dongwoon Bai, Jungwon Lee
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Abstract
An apparatus and method of low complexity optimization solver for path smoothing with constraint variation are herein disclosed. According to one embodiment, an apparatus includes an L1 central processing unit (CPU) configured to transform an L1 trend filtering problem to a primal-dual linear programming (LP) optimization problem pair; and an L1 arithmetic logic unit (ALU) connected to the L1 CPU and configured to solve a primal problem of the primal-dual LP optimization problem pair with an extended full tableau simplex method.
Claims20
An apparatus, comprising:
- an L1 central processing unit (CPU) configured to transform an L1 trend filtering problem to a primal-dual linear programming (LP) optimization problem pair;
- and
- an L1 arithmetic logic unit (ALU) connected to the L1 CPU and configured to solve a primal problem of the primal-dual LP optimization problem pair with an extended full tableau simplex method.
A method, comprising:
- transforming, by an L1 central processing unit (CPU), an L1 trend filtering problem to a primal-dual linear programming (LP) optimization problem pair;
- and
- solving, by an L1 arithmetic logic unit (ALU) connected to the L1 CPU, a primal problem of the primal-dual LP optimization problem pair with an extended full tableau simplex method.
An apparatus, comprising:
- an L2 central processing unit (CPU) configured to derive a quadratic programming (QP) problem through dual transformation;
- and
- an L2 arithmetic logic unit (ALU) connected to the L2 CPU and configured to solve the QP problem using an alternating direction method of multipliers (ADMM) based solution with closed-form updates.
A method, comprising:
- deriving, by an L2 central processing unit (CPU), a quadratic programming (QP) problem through dual transformation;
- and
- solving, by an L2 arithmetic logic unit (ALU) connected to the L2 CPU, the QP problem using an alternating direction method of multipliers (ADMM) based solution with closed-form updates.
Dependencies are inferred from the claim text.