Advanced optimization technique for scheduling IoT tasks in cloud-fog computing environments

Cosine Modulated Filter Banks (CMFB) are very popular among the different maximally decimated filter banks due to their design ease and simplicity in implementation and the property that all the coefficients of all the filters are real. All the analysis and synthesis filters are derived from one or two prototype filters. Hence, recently, the design of the prototype filter in a CMFB has become a subject of interest in the field of multirate signal processing. Perfect Reconstruction (PR) filter banks are those which can produce at the output, a weighted delayed version of the input. But in most of the applications a near perfect reconstruction (NPR) is sufficient. This can reduce the computational complexity. Different approaches developed for the efficient and optimal design of the prototype filter in a NPR orthogonal CMFB are studied, classified and summarized in this paper. In today's applications, less space and low power consumption are very essential. When the different design approaches for the design of the prototype filter in CMFB are compared, it is observed that the one using frequency response masking(FRM) and meta-heuristic optimization techniques gives better performance in terms of implementation complexity, which in turn can lead to reduced chip size and power consumption. It is hoped that this review will be highly beneficial to the researchers working in the area of multirate signal processing. At the end, we also propose some novel design approaches for the design of low complexity prototype filter using FRM technique.

Prototype Filter Design Approaches for Near Perfect Reconstruction Cosine Modulated Filter Banks - A Review

Multiswarm spiral leader particle swarm optimisation algorithm for PV parameter identification

This paper presents an improved method for designing multichannel cosine modulated filter bank (CMFB) with reduced computational complexity and low design parameters In this method, design problem of multi-channel CMFB is constructed as design of a prototype filter whose magnitude response at quadrature frequency is 0707 which is utilized for finding the optimum passband edge frequency through empirical formula instead of using single or multivariable optimization technique Performance of different adjustable window functions such as Saramaki, Ultraspherical, Cosh, Exponential and Roark's Transitional has been also examined with exploiting spline function in transition band of ideal filter response for designing CMFB The simulation results presented in this paper clearly show the key advantageous features of this algorithm as compared to other known methods

Design and performance of closed form method for cosine modulated filter bank using different windows functions

This paper proposes a new algorithm based on Gbest-guided Cuckoo Search (GCS) algorithm for the design of higher order Quadrature Mirror Filter (QMF) bank. Although the optimization of lower order filters can be performed easily by applying existing meta-heuristic optimization techniques like Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) etc., these methods are unsuccessful in searching higher order filter coefficients due to multimodality and nonlinear problem space; leads to some undesirable behaviors in filter responses like ripples in transition band, lower stop-band attenuation etc.. Comparison with other available results in the literature indicate that the proposed method exhibits an 69.02% increase in stop-band attenuation and 99.71% reduction in Perfect Reconstruction Error (PRE) of higher order filter bank. Besides, the percentage improvements in Fitness Function Evaluations (FFEs) of GCS based 55th order QMF bank design with respect to PSO, ABC and CSA are 81%, 82% and 59% respectively, and execution time is improved by 73%, 72% and 42% respectively. The simulation results also reveal that the proposed approach exhibits lowest mean and variance in different assessment parameters of filter bank and it does not require tuning of algorithmic parameters whereas in standard CSA replacement factor need to be adjusted. Further, the proposed algorithm is tested on six standard benchmark problems and complex benchmark functions from the CEC 2013 where it demonstrated significant performance improvements than other existing methods.

An efficient gbest-guided Cuckoo Search algorithm for higher order two channel filter bank design

This paper proposes an improved denoising method based on the cascaded arrangement of filters. The different combinations of filters are obtained optimally through the improved performance of the salp swarm algorithm and cascading four filters out of twelve different types of filters. The searching ability of standard salp swarm algorithm is enhanced following the strategies in differential evolution, and hence the algorithm is named as differential evolution-based salp swarm algorithm (DESSA). Most of the existing image denoising algorithms are suitable to remove either Gaussian, Salt & Pepper, or Speckle noise. Alternatively, due to the optimal combination of filters in the cascaded arrangement, the proposed denoising method exhibits its effectiveness in the removal of all three noises and the denoised images are better in terms of both quantitative analysis and visual quality. The denoising performance of the proposed method is also tested on the mixed noise which demonstrates the significant improvements compared to state-of-the-art algorithms. Further, the experiment on CEC 2014 benchmark functions indicates that the proposed DESSA achieves better optimal solutions than existing algorithms.

An improved image denoising technique using differential evolution-based salp swarm algorithm

In this paper a two channel Quadrature Mirror Filter (QMF) bank is designed using Genetic Algorithm (GA) and coefficients of filters are represented in Canonical Signed Digit (CSD). A fresh Genetic operator is used that combines crossover and adaptive mutation to improve the convergence rate and solution quality of GA. Prototype filter is constructed using GA and the coefficients of the filter are converted to nearest signed power of two terms which reduces hardware complexity of the overall system. The proposed design of QMF is also achieved least value of Reconstruction error. The technique improves the performance of QMF with respect to its peak reconstruction error, transition bandwidth and hardware required to realize FIR digital filter to less than the complexity of 2's complement representation. During the optimization of prototype filter coefficients only nonzero CSD digits are used so that better performance is achieved.

Canonical signed digit representation of Quadrature Mirror Filter using Genetic Algorithm

This work presents a proficient approach of designing an M-band Near Perfect Reconstruction (NPR) Cosine Modulated Filter Bank (CMFB) where the NPR condition is built upon to satisfy the power complementary property and the pass-edge frequency is repetitively varied to adjust the filter-coefficients to reduce the reconstruction error occurred. Using this optimal value of the pass-edge frequency, the prototype filter is designed and the filter bank is considered from that single prototype filter. Thus the primary goal of designing the CMFB comes down to the issue of implementing efficient structure of this prototype filter. Now the prototype filter is designed with Interpolated Finite Impulse Response (IFIR) technique where numbers of hardware multipliers are reduced by cascading model and image suppression filter compared to that of single prototype filter and furthermore the designed filter coefficients are replaced with Canonical Signed Digit (CSD) to get lesser hardware complexity. To make the system practically realizable, an Electrocardiogram (ECG) signal is processed through this system and reconstructed back again. Some quality measurement parameters such as Signal-to-Noise Ratio (SNR), Mean Square Error (MSE) and Percentage Root Mean Square Difference (PRD) are analyzed to see the effectiveness of the CMFB.

An IFIR approach for designing M-band NPR Cosine Modulated Filter Bank with CSD

This paper presents a novel hybrid algorithm based on Multi-swarm Cooperative Particle Swarm Optimization (MCPSO) and Simulated Annealing (SA) for the design of higher order Quadrature Mirror Filter (QMF) bank. The optimization of lower order filters can be carried out easily by traditional optimization methods, but these approaches failed to find higher order filter coefficients due to nonlinear and multimodality problem space. Most of the optimization algorithms are easily trapped into local optimum which yields few unwanted characteristics in filter magnitude responses like ripples in transition region, lower stop-band attenuation. The proposed algorithm, named Simulated Annealing-based Multi-swarm Cooperative PSO (SAMCPSO), is presented here to obtain prototype filter that leads to near-perfect reconstruction for both lower and higher dimensional filter banks. Comparison with other existing methods in the literature demonstrates that the proposed algorithm exhibits an average increase of 17.39% in stop-band attenuation and 47.35% reduction in Perfect Reconstruction Error (PRE) of 82-tap filter bank.

Design of Higher Order Quadrature Mirror Filter Bank Using Simulated Annealing-Based Multi-swarm Cooperative Particle Swarm Optimization

This paper presents an improved image-denoising technique that is based on the combination of cascaded filters. The amalgamation of different filters is acquired by using the Slime Mould Algorithm (SMA) and cascading four filters among twelve filters which provide improved denoising performance. SMA has a new and individual mathematical model and this model employs adaptive measures to stimulate the procedure of generating positive and negative feedback of the propagation wave of Slime Mould. The entire model is supported by a bio-oscillator that can build the optical path for collecting food with excellent exploitation propensity and exploratory potentiality. Different denoising techniques are suitable for either Salt & pepper, Gaussian, or Speckle noise but our proposed algorithm helps in removing all three noises. Denoised images obtained by the proposed denoising technique are far superior to denoised images obtained by other denoising techniques in the case of visual and quantitative analysis. The proposed algorithm also provides a significant improvement compared to other algorithms.

Roshni Chakrabarti

Papers

An improved image denoising technique using differential evolution-based salp swarm algorithm

Canonical signed digit representation of Quadrature Mirror Filter using Genetic Algorithm

An IFIR approach for designing M-band NPR Cosine Modulated Filter Bank with CSD

Design of Higher Order Quadrature Mirror Filter Bank Using Simulated Annealing-Based Multi-swarm Cooperative Particle Swarm Optimization

An Improved Image Denoising Technique by designing Cascaded Filter using Slime Mould Algorithm