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106 articles for “mean square error”
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Image Compression via Non-separable Discrete Fractional Fourier Transform
Abstract: The main idea behind image compression is to reduce the bandwidth for transmission and required space for storage. Thus, image compression is of great importance. In this paper we present the image compression technique using Non-Separable Discrete Fractional Fourier Transform (NSDFrFT). Numerical simulation results suggested that image compression method using NSDFrFT as transform technique gives better performance for images when compression ratio is high in comparison to DFrFT and JPEG. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 3, 2015 · pp. 1–9 Read article
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A Comprehensive survey of robust image quality metrics for satellite imagery
Abstract: Satellite imagery is essential for applications like environmental monitoring, urban development, precision agriculture, defence surveillance, and disaster response. The reliability of these applications is closely tied to the quality of the captured images, which may be compromised by atmospheric effects, sensor imperfections, compression artifacts, and transmission noise. As a result, accurate image quality assessment (IQA) is essential to ensure trustworthy analysis and informed decision-making in satellite-based systems. The distinctive properties …
Published in Research & Reviews : Journal of Space Science & Technology · Vol. 15, Issue 1, 2026 · pp. 7–20 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
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Genomic Selection for Grain Yield in Wheat Using Machine Learning on DArT Molecular Markers: A Comparative Evaluation Across Multi-Environment Trials
Abstract: Genomic selection (GS) predicts complex quantitative traits directly from genome-wide molecular markers, bypassing the need for extensive phenotypic trials and accelerating plant breeding cycles. We conducted a comparative evaluation of seven regression approaches — ridge regression (the machine-learning equivalent of RR-BLUP), Lasso, Elastic Net, Partial Least Squares, linear Support Vector Regression, Random Forest, and Gradient Boosting — for predicting grain yield from 1,279 Diversity Array Technology (DArT) molecular markers genotyped …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 2, 2026 Read article
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Password Protected Image Encryption and Decryption using Hybrid Technique for Data Security
Abstract: Abstract: Data security and data anti-corruption are some areas of cryptography which is under continuous research and development. In this paper, a password based protection scheme has been included in order to increase the level of security of data. Here a hybrid technique for data security has been proposed and compared with its non-hybrid counterparts which resulted in the hybrid technique giving better results for various parameters of study like …
Published in Current Trends in Signal Processing · Vol. 9, Issue 1, 2019 · pp. 17–25 Read article
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Application of Compressive Sensing for Sampling and Reconstruction of MRI Images
Abstract: In recent years, a new theory of compressive sensing has evolved which asserts that super resolved signals and images can be recovered with far fewer samples than that demanded by the Nyquist sampling theorem. It is required that the signal being sensed has a low information-rate meaning that it is sparse in original or some transform domain. Former approaches capture the complete signal and process it to extract the information. …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 42–48 Read article
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Efficient Partial Update Algorithm over Wireless Networks
Abstract: Adaptive partial update algorithm is developed based on incremental method. The proposed algorithm applies in real time changing environment. The proposed algorithm responds to linear estimation with nodes in cooperative manner and less number of computations. The algorithm has powerful advantage is that it requires less number of coefficient and reduced computational and communication complexity in wireless sensor network. It is efficient because it has power of solving distributed estimation …
Published in Current Trends in Signal Processing · Vol. 6, Issue 3, 2016 · pp. 1–8 Read article
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Optimization of Symmetric Linear Phase Low Pass FIR Filter Using Genetic Algorithm
Abstract: In the proposed paper, optimization of symmetric linear phase low pass Finite Impulse Response (FIR) filter using Genetic Algorithm GA is a computational optimization technique; which optimizes the Mean Square Error (MSE) and filter coefficients with the help of fitness function. The optimize results are compared with two different filter designing analysis (FDA) methods viz. least square method and equiripple method
Published in Current Trends in Signal Processing · Vol. 5, Issue 2, 2015 · pp. 9–14 Read article
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Wavelets-based Denoising by Optimizing Polynomial Threshold Function
Abstract: In this paper, a wavelets-based technique for denoising of one-dimensional signals is proposed which employs artificial bee colony (ABC) algorithm for optimizing a new polynomial threshold function. The coefficients of the threshold function are optimized dynamically to maximize the output signal to noise ratio (SNR). ABC algorithm calculates the coefficients for maximum output SNR. The proposed technique is tested for three artificial signals, namely blocks, bumps and Doppler signals. Additive …
Published in Current Trends in Signal Processing · Vol. 4, Issue 2, 2014 · pp. 11–23 Read article
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Perceptual Features Based Continuous Speech Recognition in Additive Noise Environment Using Various Modelling Techniques
Abstract: The main objective of this paper is to discuss the effectiveness of Mel frequency perceptual features and the noise reduction technique in evaluating the performance of multi speaker independent continuous speech recognition system in additive noise environment by using various modelling techniques. The proposed perceptual features are captured and trained using clustering technique, GMM, continuous density HMM and back propagation neural networks. Speech recognition system is evaluated on clean and …
Published in Current Trends in Signal Processing · Vol. 2, Issue 1-3, 2012 · pp. 67–81 Read article
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Low-light Video Enhancement with SVD-DWT Algorithm for Multimedia Surveillance Network
Abstract: After the outbreak of the global pandemic COVID-19, video surveillance has become an important aspect of multimedia communication in monitoring-based systems, security systems, object tracing etc. However, due to drawbacks like video frame distortion, the quality of the video in surveillance may be affected in some cases. In this work, a video enhancement-based multimedia surveillance network has been developed by using a Discrete Wavelet Transform (DWT) and Singular Value Decomposition …
Published in Current Trends in Signal Processing · Vol. 10, Issue 3, 2020 · pp. 42–50 Read article
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An Efficient Method of Fault Analysis using Artificial Neural Network
Abstract: In the power system, there are many techniques to identify and classify the faults. So, it is utmost important to choose the suitable technique. In this paper, a novel technique based on ANN have been proposed. When abnormal conditions occur in the system, the purposed method identifies and classify the fault to protect the system from the faults and stop from the big hazards. Simulation of purposed Simulink model have …
Published in Current Trends in Signal Processing · Vol. 11, Issue 1, 2021 · pp. 9–25 Read article
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Interference Reduction in DS-CDMA Systems Using Adaptive MMSE Technique
Abstract: Multiple access interference (MAI) limits the capacity of Direct Sequence Code Division Multiple Access (DS-CDMA) systems due to direct sequence of users. This paper examines interference reduction in Direct Sequence Code Division Multiple Access (DS-CDMA) system using Adaptive Minimum Mean Square Error (AMMSE). Much of the present research is aimed at finding an appropriate tradeoff between complexity and performance. Simulation results shows that the Adaptive MMSE is better performed than …
Published in Journal of Microelectronics and Solid State Devices · Vol. 2, Issue 3, 2015 · pp. 1–7 Read article
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ECG De-noising Techniques and Optimal Feature Selection Using Principle Component Analysis
Abstract: AbstractECG (Electrocardiography) is used to record and determine the condition of the heart. This paper provides an overview of various ECG de-noising techniques that are used to eliminate different type of noises; therefore, noise reduction procedure to be performed to eliminate different type of noises such as baseline wander, dc offset and high frequency interference, and then the pre-processed signal is used to extract features from the ECG signal. This …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 5, Issue 1, 2018 · pp. 14–20 Read article
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Nonlinear Semiconductor Device Modeling using Neural Networks
Abstract: This paper describes the nonlinear semiconductor (transistor) of small and large signal modeling using a single neural network. Multilayer perceptron (MLP) with back-propagation (BP) learning is adopted in this work to model the drain current (ID) and the transconductance (gm) of the transistor. MLP modeling performance in terms of mean square error (MSE) and complexity of the network are illustrated briefly. Artificial neural network (ANN) model outcome for nonlinear function …
Published in Journal of VLSI Design Tools and Technology · Vol. 4, Issue 3, 2014 · pp. 1–6 Read article
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Development of System for Speech Enhancement using Combinational Adaptive LMS on Reconfigurable Platform
Abstract: Low cost and robustness makes the least mean square (LMS) algorithm most popular. Improved adaptive filter performance can be obtained by combinational approach. In this paper, for speech enhancement, we used one of such approaches known as ‘filter combination’. As our simulation results show, Fixed-Sign LMS algorithm overcome other algorithms in terms of SNR and mean square error. Keywords: Adaptive filter, speech enhancement, windows, convex combination
Published in Journal of VLSI Design Tools and Technology · Vol. 6, Issue 3, 2016 · pp. 28–34 Read article
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Rainfall-runoff Modeling using HEC-HMS Hydrologic Model for Guder River Watershed, Blue Nile Basin, Ethiopia
Abstract: Rainfall-runoff modeling is important for a number of hydrologic applications including flood forecasting, water resource planning and management. This study presents the result of a watershed rainfall-runoff modeling for Guder river watershed having area of 6597 km 2 using Hydrologic Engineering Center-Hydrologic Modeling Systems (HEC-HMS). The watershed runoff is varying spatially and temporally due to manmade factors and natural factors on the watershed. These issue needs efficient water resource planning …
Published in Journal of Water Resource Engineering and Management · Vol. 8, Issue 2, 2021 · pp. 62–77 Read article
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Reduction of Ocular Artifacts in Single Channel EEG by EEMD-IMF Thresholding
Abstract: AbstractElectroencephalogram (EEG) is a widely used signal for analyzing the activities of the brain and usually contaminated with artifacts due to the movements of eye, heart, muscles and power line interference. Among these ocular activities creates significant artifacts and makes the analysis difficult. In this paper, ensemble empirical mode decomposition (EEMD) inspired by wavelet thresholding is used for the correction of ocular artifacts (OA) in EEG signals. Unlike the conventional …
Published in Recent Trends in Electronics Communication Systems · Vol. 5, Issue 1, 2018 · pp. 17–25 Read article
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Comparative Analysis of Digital Image Watermarking using DCT and DWT
Abstract: AbstractWatermarking is a technique to hide information into digital data and provides security against intentional and unintentional attack. It is a very important and emerging field which helps to protect ownership of digital information. Watermarking is the process of inserting or hiding information behind cover data. In this paper we discussed about two digital watermarking techniques, Discrete Cosine Transform (DCT) and discrete wavelet Transform (DWT). The parameters to test robustness …
Published in Journal of Communication Engineering & Systems · Vol. 4, Issue 1, 2014 · pp. 1–5 Read article
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Zoom Based Image Super-Resolution: Using Two Level DWT as Feature Model
Abstract: AbstractIn this paper we present an algorithm of super-resolution (SR) imaging to reconstruct high-resolution (HR) image from sequence of low-resolution (LR) images of static scene captured at the different camera zoom factor. The resultant HR image is constructed at the resolution of the most zoomed LR image. In the proposed approach algorithm uses LR images of the static scene captured at three distinct zoom-factors. Learning based SR technique is used …
Published in Journal of Communication Engineering & Systems · Vol. 9, Issue 2, 2019 · pp. 95–105 Read article