Nikhil Agrawal
@iiitn.ac.in
Assistant Professor, Dept. of Electronics and Communication Engineering
Indian Institute of Information Technology Nagpur
EDUCATION
M. Tech. and Ph.D. from PDPM IIITDM Jabalpur
RESEARCH INTERESTS
Signal Prcessing
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Nikhil Agrawal, Thomas Patrick, Matthew Davis, Md Ahiduzzaman, and Amit Kumar
Informa UK Limited
Abstract Freshwater is a critical natural resource and fundamental to social and environmental activities, including industrial activities, food production, and residential needs. Hence, it is important to understand provincial water supply and demand. However, there are large gaps in provincial and sectoral water use data. This study provides estimates for disaggregated water use by regional subsectors and uses Sankey diagrams to depict the water flow from intake to consumption and discharge. The study uses a bottom-up method in the oil and gas and hydropower sectors and top-down methods in the residential, commercial and institutional, manufacturing, mining, agricultural, and power sectors. Surface and ground water are considered separately. Water use in the year 2017 was analyzed for British Columbia, Alberta, Saskatchewan, Manitoba, Ontario, Quebec, the Atlantic Provinces, and the Territories. Water-use intensities were also calculated by region and sector. A total of 40 billion m3 of water use is traced from source to either discharge or consumption. New disaggregated data is developed provincially and by sector for oil and gas, mining, and power generation. Water use in the oil and gas sector was disaggregated into 5 subsectors, with oil sands surface mining in Alberta as the largest consumer with 138 million m3 of water consumed. Hydro power was estimated to consume the most water out of all sectors, with 3393 million m3 of water consumed. Alberta was also found to have the largest consumptive water use per capita. The results provide important insights on water supply and demand in Canada. Such information supports both regional and federal governments in formulating appropriate regional and sectoral policies and can support water managers and the public in understanding water supply and demand in Canada. Modelling efforts requiring regional and sectoral water use can also use these results. Supplemental data for this article is available online at http://dx.doi.org/.
Nikhil Agrawal, Anil Kumar, B. Kuldeep, S. Lee, and H. N. Lee
Springer Science and Business Media LLC
N. Agrawal, A. Kumar, V. Bajaj and G. Singh
Kuldeep Baderia, A. Kumar, Nikhil Agrawal, and Ranjeet Kumar
IEEE
In this work, a new approach lean on minor component analysis (MCA) neural learning and fractional derivative (FD) is introduced for the design of digital finite impulse response (FIR) filters. In this method, design problem is modeled as summation of integral error in passband and stopband region in term of polyphase components (PCs) of a FIR filter in frequency domain, which is solved by an efficient machine learning algorithm called minor component analysis (MCA) neural learning. For more accurate frequency response, fractional derivative is applied at a reference point in passband, and the resulted fractional derivative constraints (FDCs) are optimized by particle swarm based techniques, using an objective function formulated as summation of maximum error in pass band and stop band region and stopband attenuation (in magnitude) of a FIR filter. The comparative study with recently published results evidence the impact of proposed method.
N. Agrawal, A. Kumar, and Varun Bajaj
Springer Science and Business Media LLC
Anil Kumar, Nikhil Agrawal, Ila Sharma, Seungchan Lee, and Heung-No Lee
Institute of Electrical and Electronics Engineers (IEEE)
This paper presents a new efficient method for implementing the Hilbert transform using an all-pass filter, based on fractional derivatives (FDs) and swarm optimization. In the proposed method, the squared error difference between the desired and designed responses of a filter is minimized. FDs are introduced to achieve higher accuracy at the reference frequency (<inline-formula> <tex-math notation="LaTeX">$\\boldsymbol {\\omega }_{\\mathbf {0}}$ </tex-math></inline-formula>), which helps to reduce the overall phase error. In this paper, two approaches are used for finding the appropriate values of the FDs and reference frequencies. In the first approach, these values are estimated from a series of experiments, which require more computation time but produce less accurate results. These experiments, however, justify the behavior of the error function, with respect to the FD and <inline-formula> <tex-math notation="LaTeX">$\\boldsymbol {\\omega }_{\\mathbf {0}}$ </tex-math></inline-formula>, as a multimodal and nonconvex problem. In the second approach, a variant of the swarm-intelligence-based multimodal search space technique, known as the constraint-factor particle swarm optimization, is exploited for finding the suitable values for the FD and <inline-formula> <tex-math notation="LaTeX">$\\boldsymbol {\\omega }_{\\mathbf {0}}$ </tex-math></inline-formula>. The performance of the proposed FD-based method is measured in terms of fidelity aspects, such as the maximum phase error, total squared phase error, maximum group delay error, and total squared group delay error. The FD-based approach is found to reduce the total phase error by 57% by exploiting only two FDs.
Nikhil Agrawal, Anil Kumar, and Varun Bajaj
Institute of Electrical and Electronics Engineers (IEEE)
In this paper, a new design method for digital infinite impulse response ( IIR ) filters with nearly linear-phase response is presented using fractional derivative constraints ( FDCs ) . In the proposed method, design problem of an IIR filter is constructed as the minimization of phase error between the desired and designed phase response of an allpass filter ( APF ) such that the designed lowpass filter ( LPF ) or highpass filter ( HPF ) yields less passband ( ep ) , and stopband errors ( es ) with optimal stopband attenuation ( As ) . In order to have accurate passband ( pb ) response, FDCs are imposed on appropriate reference frequency, where the optimality of these FDCs are ensured by using a new greedy based sorting mechanism. The simulated results reflect the efficiency of the proposed method in term of improved passband response along with better transition width. However, small reduction in As is observed within the allowable limit, when compared to non-fractional design approach, but the designed filter remains immune to wordlength ( WL ) effect.
Anil Kumar, N. Agrawal, and I. Sharma
Springer Singapore
N. Agrawal, A. Kumar, and Varun Bajaj
Springer Science and Business Media LLC
Nikhil Agrawal, Anil Kumar, Varun Bajaj, and G. K. Singh
Institute of Electrical and Electronics Engineers (IEEE)
In this paper, a new design method for digital bandpass and bandstop infinite impulse response filters with nearly linear-phase response is proposed. In this method, the phase response of an all-pass filter is optimized in the frequency domain to yield less passband error <inline-formula><tex-math notation="LaTeX">${\\text{Er}}_{p}$</tex-math> </inline-formula> and stopband error <inline-formula><tex-math notation="LaTeX">${\\text{Er}}_{s}$</tex-math> </inline-formula> with optimal stopband attenuation <inline-formula><tex-math notation="LaTeX">$A_{s}$</tex-math> </inline-formula>. To achieve high accuracy in passband and stopband regions, fractional derivative (FD) constraints are evaluated in the respective regions, and the filter coefficients are computed using the Lagrange multiplier method. The behavior of fidelity parameters measured in terms of <inline-formula><tex-math notation="LaTeX"> ${\\text{Er}}_{p}{,\\text{Er}}_{s}$</tex-math></inline-formula>, and phase error <inline-formula> <tex-math notation="LaTeX">${\\text{Er}}_{{\\text{ph}}}$</tex-math></inline-formula> is multimodel w.r.t. FD values. Therefore, modern heuristic technique, known as cuckoo search optimization is used for determining the optimal value of FDs and reference frequency simultaneously to minimize the fitness function, which is constructed as a sum of the squared error in passband and stopband. The designed filter yields up to 60% reduction in <inline-formula> <tex-math notation="LaTeX">${\\text{Er}}_{p}$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX"> ${\\text{Er}}_{{\\text{ph}}}$</tex-math></inline-formula> in the case of bandpass filter. Meanwhile, the response of filter is not degraded due to the finite word length effect.
N. Agrawal, A. Kumar, and Varun Bajaj
IEEE
In this paper a new design approach for an infinite impulse response (IIR) filter is devised using two allpass filters (APFs). In the proposed method, the design problem is constructed in least squares (LS) sense of phase response error in frequency domain for both APF. Fractional derivative (FD) is incorporated as constraint in the design procedure, which improved the approximation of the designed phase response with desired phase response. Exploration of suitable value of FD (u) and its point of evaluation known as reference frequency ($\\omega_{\\mathbf{o}}$) is computationally expensive task when searched using conventional search approach. Therefore, heuristic optimization methods known as constraint factor particle swarm optimization (CF-PSO) has been deployed for the task such that the objective function constructed as sum of maximum phase errors of both APFs must minimized. Experiment revels that 8th order FD is an appropriate order for the design of a lowpass filter (LPF).
S. Ansari, G. Kishor, P. K. Verma, N. Agrawal, I. Sharma, and A. Kumar
IEEE
In this paper, modified cuckoo search (MCS) algorithm is employed for the efficient design of infinite impulse response (IIR) filter by minimizing a fitness function. The fitness function is constructed as mean squared error between ideal and obtained response of the filter. In addition to this, proposed method gives minimum number of adders through canonical signed digit (CSD), and hence makes hardware requirements cost effective. The stability of filter is achieved by incorporating lattice structure because it is easy to perform, when compared with decomposition in small order approach. Efficiency of the filter is found enhanced by comparing the fidelity parameters with previous algorithm, and a detailed analysis is carried with different types of filter.
I. Sharma, N. Agrawal, A. Kumar and L. Balyan
In this paper, an optimal design of adder efficient multiplierless non-uniform filterbank (FB) is presented with the aid of Chebyshev polynomials and hybrid optimization. An objective function is modelled for designing a prototype filter to achieve a magnitude response of 0.7071 at 3-dB cutoff frequency $(\\boldsymbol{\\omega}_{\\boldsymbol{c}})=\\boldsymbol{\\pi}/(2\\cdot \\boldsymbol{M})$. Thus, the design problem is formulated as a minimization of integral mean-square error (MSE), computed as a difference of the ideal response and designed response. On differentiation with respect to filter coefficients leads to linear equations. Hybrid optimization algorithm has been used to get optimum values of weighting factors ($\\boldsymbol{K_{P}}$ and $\\boldsymbol{K_{S}}$). For adder minimization, a newly proposed hybrid common sub-expression elimination (CSE) technique is also used and the simulation results obtained are also compared with other algorithms. It has found that the proposed filter attains high adder gain with improved reconstruction error.
N. Agrawal, A. Kumar and V. Bajaj
N. Agrawal, Ahiduzzaman and Amit Kumar
Nikhil Agrawal, Anil Kumar, and Varun Bajaj
Institute of Electrical and Electronics Engineers (IEEE)
In this paper, a new design method based on fractional derivative (FD) is proposed for designing digital stable infinite impulse response (IIR) filters with nearly linear-phase response. In this method, the design problem is formulated as a phase error optimization of an all-pass filter connected in parallel with a pure delay function. FD is employed to improve the frequency response of the filter at some reference point <inline-formula> <tex-math notation="LaTeX">$(\\omega _{{0}})$</tex-math></inline-formula> in the passband. Optimal values of FD constraints and reference points in passband are determined by minimizing the sum of error in passband <inline-formula> <tex-math notation="LaTeX">$(E_{p})$</tex-math></inline-formula> and stopband <inline-formula> <tex-math notation="LaTeX">$(E_{s})$</tex-math></inline-formula> of an IIR filter, using different evolutionary techniques such as particle swarm optimization (PSO), constraint factor inertia PSO (CFI-PSO), quantum PSO, artificial bee colony algorithm, and cuckoo search technique. Comparative study provides evidence that the proposed method, based on CFI-PSO, gives the best performance amongst the employed swarm-based techniques. Experimental results show the impact of the proposed method as compared to earlier reported techniques in terms of improved response in passband and sharper transition width. However, small reduction in stopband attenuation <inline-formula><tex-math notation="LaTeX"> $(A_{s})$</tex-math></inline-formula> is observed within the allowable limit when compared to nonfractional design approaches.
N. Agrawal, A. Kumar, V. Bajaj, and G. K. Singh
Springer Science and Business Media LLC
N. Agrawal, A. Kumar, and Varun Bajaj
IEEE
In this paper, an optimal design of digital infinite impulse response (IIR) with controlled ripple responses in passband (pb) and stopband (sb) is presented. An improved error function defined as mean squared error (MSE) between ideal and designed responses of a filter along with controlled ripple in passband and stopband is proposed and minimized. It is optimized using cuckoo search (CS) algorithm, which is tuned by experimental analysis. The results obtained reveals that high stopband attenuation (As) can be achieved using the controlled ripple, however the passband error (ep) and stopband error (es) are also increased.
N. Agrawal, A. Kumar, Varun Bajaj, and H.-N. Lee
IEEE
In this paper, an improved technique for the design of digital infinite impulse response (IIR) filter with controlled ripple response in passband and stopband is presented. A new error function based on the minimization of squared error difference between desired and designed responses of filter with controlled ripple in passband (pb) and stopband (sb), is proposed and for optimizing the error function, a new hybrid optimization technique based on artificial bee colony (ABC) algorithm and quantum particle swarm optimization (QPSO) is proposed. Stability of the designed filter is guaranteed with less complex structure utilized during iterative computation. A comparative study of performance of the developed hybrid technique with classical methods is presented that illustrates the improved performance of the proposed method.
N. Agrawal, Abhishek Kumar and V. Bajaj
In this paper, a meta-heuristic algorithm known as artificial bee colony (ABC) algorithm is employed for the design of digital infinite impulse response (IIR) filter based on nonlinear minimization of mean square error (MSE) between the ideal and desired responses of the filter. In this method, stability of IIR filter during design is assured by using lattice structure as it makes easy to maintain the stability with less computation cost. In addition to this, it also helps in designing higher order filter with better search capability. Performance of the algorithm is justified by comparing the fidelity parameter with existing algorithms, followed by a detailed analysis of different types of filter.
N. Agrawal, A. Kumar, and V. Bajaj
IEEE
In this paper, a hybrid optimization for the design infinite impulse response (IIR) filter employing particle swarm optimization (PSO) and artificial bee colony (ABC) algorithm is presented. The design problem is formulated as a mean square error between desired response and ideal response. For the stability of filter, a lattice structure in design is utilized. A comparative study of performance of PSO and its different variants is also made which shows improved efficiency of hybrid method in the field of IIR filter design.