AbstractIn this paper, we show that accepting networks of splicing processors (ANSPs) of size 2 are computationally complete. Since, by definition, an ANSP needs at least two nodes to perform non-trivial computations, this completely settles the question of designing complete ANSPs of minimal size. Also, we derive from this result the fact that all the languages in PSPACE can be accepted by ANSPs of size 2, having polynomial length complexity (the ANSP complexity measure for the space used in a computation). However, the construction that we propose, although efficient from the descriptional complexity and space complexity points of view, does not seem to have good properties from the time complexity point of view. In this respect, we prove...
AbstractIn search for a universal splicing system, in this paper we present a Post system universal ...
AbstractA hybrid network of evolutionary processors (an HNEP) is a graph where each node is associat...
We consider time complexity classes defined on accepting hybrid networks of evolutionary processors...
AbstractIn this paper, we show that accepting networks of splicing processors (ANSPs) of size 2 are ...
AbstractIn this paper we consider a new, bio-inspired computing model: the accepting network of spli...
AbstractThe Accepting Networks of Evolutionary Processors (ANEPs for short) are bio-inspired computa...
In this paper, we present some results regarding the size complexity of Accepting Networks of Evolut...
AbstractThis paper proposes a notion of time complexity in splicing systems. The time complexity of ...
In this paper, we introduce generating networks of splicing processors (GNSP for short), a...
This paper presents the model named Accepting Networks of Evolutionary Processors as NP-problem sol...
AbstractWe propose a computational model that is inspired by genetic operations over strings such as...
We consider three complexity classes defined on Accepting Hybrid Networks of Evolutionary Processor...
AbstractThe goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the ma...
Networks of splicing processors (NSP for short) embody a subcategory among the new computational mod...
In this paper we simplify a recent model of computation considered in [Margenstern et al. 2005], nam...
AbstractIn search for a universal splicing system, in this paper we present a Post system universal ...
AbstractA hybrid network of evolutionary processors (an HNEP) is a graph where each node is associat...
We consider time complexity classes defined on accepting hybrid networks of evolutionary processors...
AbstractIn this paper, we show that accepting networks of splicing processors (ANSPs) of size 2 are ...
AbstractIn this paper we consider a new, bio-inspired computing model: the accepting network of spli...
AbstractThe Accepting Networks of Evolutionary Processors (ANEPs for short) are bio-inspired computa...
In this paper, we present some results regarding the size complexity of Accepting Networks of Evolut...
AbstractThis paper proposes a notion of time complexity in splicing systems. The time complexity of ...
In this paper, we introduce generating networks of splicing processors (GNSP for short), a...
This paper presents the model named Accepting Networks of Evolutionary Processors as NP-problem sol...
AbstractWe propose a computational model that is inspired by genetic operations over strings such as...
We consider three complexity classes defined on Accepting Hybrid Networks of Evolutionary Processor...
AbstractThe goal of this paper is twofold. Firstly, to survey in a systematic and uniform way the ma...
Networks of splicing processors (NSP for short) embody a subcategory among the new computational mod...
In this paper we simplify a recent model of computation considered in [Margenstern et al. 2005], nam...
AbstractIn search for a universal splicing system, in this paper we present a Post system universal ...
AbstractA hybrid network of evolutionary processors (an HNEP) is a graph where each node is associat...
We consider time complexity classes defined on accepting hybrid networks of evolutionary processors...