Solving subset sum by spiking neural P systems with astrocytes producing calcium
We consider spiking neural P systems with astrocytes producing calcium that differs from the standard spiking neural P systems in several ways: we have a new type of resources called calcium unit alongside the standard spike, we have a new type of ...
On the power of boundary rule application in membrane computing
In this paper, it is investigated how different features of membrane systems can be simulated by the boundary rule application. Firstly, it is discussed how the effect of maximally parallel mode can be obtained by non-cooperative boundary rules ...
About reversibility in sP colonies and reaction systems
In this paper, we study reversibility in sP colonies and in reaction systems. sP colony is a bio-inspired computational model formed from an environment and a finite set of agents. The current state of the environment is represented by a finite ...
Spiking neural P systems and their semantics in Haskell
We use the functional programming language Haskell to design semantic interpreters for the spiking neural P systems. Haskell provides an appropriate support for implementing the denotational semantics of a concurrent language inspired by the ...
Automatic design of arithmetic operation spiking neural P systems
As one of the most widely studied membrane systems, a spiking neural P system consists of three fundamental elements: initial spikes, evolution rules and connection between neurons. The automatic design of an arithmetic operation spiking neural P ...
Estimation of minimum viable population for giant panda ecosystems with membrane computing models
Even though the giant panda’s extinction status is downgraded from endangered to vulnerable, but the animals still face an uphill battle for survival. Moreover, the number of giant pandas is also rare. With the increase of captive individuals, ...
Face illumination normalization based on generative adversarial network
- Dequan Guo,
- Lingrui Zhu,
- Shenggui Ling,
- Tianxiang Li,
- Gexiang Zhang,
- Qiang Yang,
- Ping Wang,
- Shiqi Jiang,
- Sidong Wu,
- Junbao Liu
Face recognition technology has been widely used in the field of artificial intelligence. The technology needs to be carried out normally under the appropriate light, however, there is not ideal light, even poor-lighted for the face recognition ...
Bio-inspired modelling as a practical tool to manage giant panda population dynamics in captivity
The highly endangered giant panda (Ailuropoda melanoleuca) is the world’s most widely recognised conservation icon. Population dynamics models can get on track to a healthy population for giant pandas, and assess its development over time. This ...
Feature selection algorithm based on P systems
Since the number of features of the dataset is much higher than the number of patterns, the higher the dimension of the data, the greater the impact on the learning algorithm. Dimension disaster has become an important problem. Feature selection ...
Morphogenetic computing: computability and complexity results
A morphogenetic (M) system is an abstract computational model combining properties of membrane (P) systems, such as computing via abstract particles in separate compartments regulating their workflow, with algorithmic self-assembly generalizing ...
GPU simulations of spiking neural P systems on modern web browsers
- Arian Allenson M. Valdez,
- Filbert Wee,
- Ayla Nikki Lorreen Odasco,
- Matthew Lemuel M. Rey,
- Francis George C. Cabarle
In this work we present a novel and proof of concept Spiking Neural P system (for short, SN P systems) simulator that runs on modern web browsers whilst using graphics processing units (for short, GPUs). By creating an SN P system that both ...
A tutorial on the formal framework for spiking neural P systems
The model of Spiking Neural P systems (SNP systems) is a widespread computational model in the area of membrane computing. It has numerous applications, especially related to machine learning. Most of these applications require a custom variant of ...
Deep learning networks with rough-refinement optimization for food quality assessment
Food quality assessment is an important part of the food industry. The traditional food quality assessment technologies have the limitations of inconsistent and different technical defects for each method. Data mining technology has significant ...