More specifically, we focus onto a key element that may help driving their efficient design and implementation: i.e., the set of building blocks that should include a generic scheduling system and its interconnections, a set collectively known as the architecture of a system.
Once the set of basic building blocks is implemented, interactions between biological elements of the model can be changed by replacing one building block by another, and new elements can be added as instances of the appropriate kind of building blocks, all this with minimal changes in the implementation of the model.
The framework is more than a set of building blocks that facilitate the production of flexible and efficient implementations of heuristic search algorithms.
The performances of the eight kinds of building blocks depend strongly on the building-block slenderness.
The implementation of these building blocks in the design of a 2-layered skin model (2LSM) is also presented in this work.
This approach separates the executable model into two distinct parts: the definition of the interactions between proteins such as activation or inhibition, and the internal implementation of the building blocks.
We present an analog very large scale integration (VLSI) implementation of a building block for a multi-chip neuromorphic hardware model of selective attention.
Thus, it is the purpose of this work to first of all describe and analyze the implementation of the essential building blocks of QLMs, and to discuss the minimal settings which are required to observe precursors of the physical phenomena outlined above.
However, the flexibility of this model allows for easy implementation of more complex building blocks such as Maxwell elements, given valid, experimentally derived element parameters.
Similar to the current operations implemented in the ASTRA toolbox, our work will enable the rapid design and implementation of distributed advanced reconstruction algorithms, using the distributed FP, BP and SIRT implementations as building blocks.
