Add to ORKGThis dissertation presents a novel design of a hardware classifier based on combining modified Ashenhurst-Curtis Decomposition and multiplexer-based synthesis. The PSUD classifier brings three new contributions: an approach to solve the column multiplicity problem, an approach to encode multiple-valued variables, and a decomposition algorithm based on modified Ashenhurst-Curtis Decomposition. One of the biggest challenges in Boolean function decomposition is the variable partitioning problem. Thus, we introduce a new representation of two combined classifiers for multiple-valued functions to overcome the variable partitioning problem which allows finding the minimal column multiplicity and consequently to find high quality decompositions le...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
General functional decomposition is mainly perceived as a logic synthesis method for implementing Bo...
Learning Hardware approach involves creating a computational network based on feedback from the env...
This paper presents a novel design of a hardware classifier based on combining modified Ashenhurst-C...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
This paper considers minimization of incompletely spec-ified multi-valued functions using functional...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
In this technical report we presented a novel approach to machine learning. Once the new framework i...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
AbstractSo far, multiple classifier systems have been increasingly designed to take advantage of har...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
General functional decomposition is mainly perceived as a logic synthesis method for implementing Bo...
Learning Hardware approach involves creating a computational network based on feedback from the env...
This paper presents a novel design of a hardware classifier based on combining modified Ashenhurst-C...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
This paper considers minimization of incompletely spec-ified multi-valued functions using functional...
The authors propose a learning-hardware approach as a generalization of evolvable hardware. A massiv...
In this technical report we presented a novel approach to machine learning. Once the new framework i...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
AbstractSo far, multiple classifier systems have been increasingly designed to take advantage of har...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
For Part 1 see ibid. vol.22, no.3 (2002). A massively parallel reconfigurable processor speeds up th...
General functional decomposition is mainly perceived as a logic synthesis method for implementing Bo...
Learning Hardware approach involves creating a computational network based on feedback from the env...