Depth-first iterative-deepening: an optimal admissible tree search
Artificial Intelligence
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
The art of computer programming, volume 2 (3rd ed.): seminumerical algorithms
A characterization of important algorithms for quantum-dot cellular automata
Information Sciences: an International Journal
Prolog (3rd ed.): programming for artificial intelligence
Prolog (3rd ed.): programming for artificial intelligence
Computer aided design (CAD) using logic programming
DAC '84 Proceedings of the 21st Design Automation Conference
Towards Multistate Nanocomputing: The Implementation of a Primitive Fuzzy Controller
ICQNM '08 Proceedings of the Second International Conference on Quantum, Nano and Micro Technologies (ICQNM 2008)
Management agent for search algorithms with surface optimization applications
WSEAS Transactions on Computers
Benchmarking in digital circuit design automation
WSEAS Transactions on Circuits and Systems
Towards the bottom-up concept: Extended quantum-dot cellular automata
Microelectronic Engineering
Toward in vivo digital synchronous sequential circuits
WSEAS Transactions on Circuits and Systems
Adder designs using reversible logic gates
WSEAS Transactions on Circuits and Systems
The key elements of logic design in ternary quantum-dot cellular automata
UC'11 Proceedings of the 10th international conference on Unconventional computation
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This paper treats the problems involved in the design of logic circuits based on novel processing platform. It begins with description of the ternary quantum-dot cell, an extended classic binary cell. These cells are basic building blocks of quantum-dot cellular automata. They are used to construct simple structures with inputs and output which implement some ternary logic function. These structures are employed as building blocks of larger and more complex circuits. The computer-aided design tool that finds an optimal implementation of a circuit by bottom-up approach is described. The search of a solution is based on iterative deepening. Since searching over all possible solutions is too computationally complex, heuristics are used to reduce the computation time.