Two two-function minimax theorems are proved. The concavity-convexity conditions of the two functions involve strictly monotone transformations and mixing of the values of the two functions, and are described by the i...Two two-function minimax theorems are proved. The concavity-convexity conditions of the two functions involve strictly monotone transformations and mixing of the values of the two functions, and are described by the inequalities as upward and weakly downward conditions.展开更多
A two-function minimax theorem is proved. In this result, the concavity-convexity conditions of both functions involve monotone transforms and mixing of functional values, and the ＂w- upwardness/w-downwardness＂ cond...A two-function minimax theorem is proved. In this result, the concavity-convexity conditions of both functions involve monotone transforms and mixing of functional values, and the ＂w- upwardness/w-downwardness＂ conditions; both spaces are required to be compact topological spaces but without linear structure. By this result, an open question proposed by Forgo and Joo in 1998 is answered.展开更多
Abstract In this paper, we study the Lp mapping properties of certain class of maximal oscillatory singular integral operators. We prove a general theorem for a class of maximal functions along surfaces. As a conseque...Abstract In this paper, we study the Lp mapping properties of certain class of maximal oscillatory singular integral operators. We prove a general theorem for a class of maximal functions along surfaces. As a consequence of such theorem, we establish the Lp boundedness of various maximal oscillatory singular integrals provided that their kernels belong to the natural space L log L（Sn-1）. Moreover, we highlight some additional results concerning operators with kernels in certain block spaces. The results in this paper substantially improve previously known results.展开更多
The stability of a periodic oscillation and the global exponential class of recurrent neural networks with non-monotone activation functions and time-varying delays are analyzed. For two sets of activation functions, ...The stability of a periodic oscillation and the global exponential class of recurrent neural networks with non-monotone activation functions and time-varying delays are analyzed. For two sets of activation functions, some algebraic criteria for ascertaining global exponential periodicity and global exponential stability of the class of recurrent neural networks are derived by using the comparison principle and the theory of monotone operator. These conditions are easy to check in terms of system parameters. In addition, we provide a new and efficacious method for the qualitative analysis of various neural networks.展开更多
In this paper, we characterize lower semi-continuous pseudo-convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the pseudo-monotonicity of its Clarke-Rockafellar Su...In this paper, we characterize lower semi-continuous pseudo-convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the pseudo-monotonicity of its Clarke-Rockafellar Sub-differential. We extend the results on the characterizations of non-smooth convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the monotonicity of its sub-differentials to the lower semi-continuous pseudo-convex functions on real Banach spaces.展开更多
This paper shows that monotone self-dual Boolean functions in irredundant disjuntive normal form （IDNF） do not have more variables than disjuncts. Monotone self-dual Boolean functions in IDNF with the same number of...This paper shows that monotone self-dual Boolean functions in irredundant disjuntive normal form （IDNF） do not have more variables than disjuncts. Monotone self-dual Boolean functions in IDNF with the same number of variables and disjuncts are examined. An algorithm is proposed to test whether a monotone Boolean function in IDNF with n variables and n disjuncts is self-dual. The runtime of the algorithm is O（n3）.展开更多
文摘Two two-function minimax theorems are proved. The concavity-convexity conditions of the two functions involve strictly monotone transformations and mixing of the values of the two functions, and are described by the inequalities as upward and weakly downward conditions.
基金Supported by Beijing Educational Committee (Grant No. KM200610005014)
文摘A two-function minimax theorem is proved. In this result, the concavity-convexity conditions of both functions involve monotone transforms and mixing of functional values, and the ＂w- upwardness/w-downwardness＂ conditions; both spaces are required to be compact topological spaces but without linear structure. By this result, an open question proposed by Forgo and Joo in 1998 is answered.
文摘Abstract In this paper, we study the Lp mapping properties of certain class of maximal oscillatory singular integral operators. We prove a general theorem for a class of maximal functions along surfaces. As a consequence of such theorem, we establish the Lp boundedness of various maximal oscillatory singular integrals provided that their kernels belong to the natural space L log L（Sn-1）. Moreover, we highlight some additional results concerning operators with kernels in certain block spaces. The results in this paper substantially improve previously known results.
基金Supported by the Natural Science Foundation of Hubei Province (2007ABA124)the Youth Project Foundation of Hubei Province Education Department (Q200722001)the Major Foundation of Hubei Province Education Department (D200722002)
文摘The stability of a periodic oscillation and the global exponential class of recurrent neural networks with non-monotone activation functions and time-varying delays are analyzed. For two sets of activation functions, some algebraic criteria for ascertaining global exponential periodicity and global exponential stability of the class of recurrent neural networks are derived by using the comparison principle and the theory of monotone operator. These conditions are easy to check in terms of system parameters. In addition, we provide a new and efficacious method for the qualitative analysis of various neural networks.
文摘In this paper, we characterize lower semi-continuous pseudo-convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the pseudo-monotonicity of its Clarke-Rockafellar Sub-differential. We extend the results on the characterizations of non-smooth convex functions f : X → R ∪ {+ ∞} on convex subset of real Banach spaces K ⊂ X with respect to the monotonicity of its sub-differentials to the lower semi-continuous pseudo-convex functions on real Banach spaces.
文摘This paper shows that monotone self-dual Boolean functions in irredundant disjuntive normal form （IDNF） do not have more variables than disjuncts. Monotone self-dual Boolean functions in IDNF with the same number of variables and disjuncts are examined. An algorithm is proposed to test whether a monotone Boolean function in IDNF with n variables and n disjuncts is self-dual. The runtime of the algorithm is O（n3）.
