Back propagation neural network (BPNN) algorithm is a widely used technique in training artificial neural networks. It is also a very popular optimization procedure applied to find optimal weights in a training process. However, traditional back propagation optimized with Levenberg marquardt training algorithm has some drawbacks such as getting stuck in local minima, and network stagnancy. This...

This paper presents a novel approach of designing linear phase FIR low pass filter using cuckoo Search Algorithm (CSA). FIR filter design is a multi-modal optimization problem. The conventional optimization techniques are not efficient for digital filter design. An iterative method is introduced to find the best solution of FIR filter design problem.Flat passband and high stopband attenuation a...

Cuckoo optimization Algorithm (COA) is employed for the optimization of linear and nonuniform circular antenna arrays. COA is a novel nature inspired computing algorithm which is motivated by the life of Cuckoo. Like other nature-inspired algorithms, COA is also a population-based method and uses a population of solutions to proceed to the global solution. The method of COA is used to determine...

Most optimization problems in real life applications are often highly nonlinear. Local optimization algorithms do not give the desired performance. So, only global optimization algorithms should be used to obtain optimal solutions. This paper introduces a new nature-inspired metaheuristic optimization algorithm, called Hoopoe Heuristic (HH). In this paper, we will study HH and validate it again...

Probabilistic data structures are so popular in membership queries, network applications, and so on. Bloom Filter and Cuckoo Filter are two popular space efficient models that incorporate in set membership checking part of many important protocols. They are compact representation of data that use hash functions to randomize a set of items. Being able to store more elements while keeping a reaso...