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In communication systems, distortion and noise are the main reason to decrease the reliability of the system, these distortions occurs because of the hardware deficiencies. In Wireless ad hoc network, connectivity and coverage area the two biggest issues. Therefore, this paper gives the practical analysis of the hardware deficiencies on hoping transmission, which amplifies and sends the better signal for the static and dynamic gain of the nodes and determine the localization of isolation nodes, improve connectivity and coverage area by reducing Nakagami-m fading. The outage possibility obtained in practical is by the signal to noise with the distortion noise, where these achieve the hardware deficiencies in the initial node and the relay node. In the same way, we consider the ergodic capability, in which hops are not dependent but it also assigns the ‘Nakagami-m’fading effect in the communication system. In this, the SNR and the signal to noise with distortion is more, which are continuous, where these are inversely proportional for the amount of hardware deficiencies. Theoretical transceivers will not satisfy the requirements in practically therefore in this paper, we provide some of the basic rules which is very helpful for the better communication in practical manner while focusing on ‘Nakagami-m’ fading effect in improving connectivity and coverage are in wireless ad-hoc networks.

In this paper, we propose an adaptive wavelet packet (WP) thresholding method with iterative Kalman filter (IKF) and Curvelet transformer for speech enhancement. The WP transform is first applied to the noise corrupted speech on a frame-by-frame basis, which decomposes each frame into a number of sub-bands. For each sub-band, a voice activity detector (VAD) is designed to detect the voiced/unvoiced parts of the speech. Based on the VAD result, an adaptive thresholding scheme is then utilized to each sub-band speech to obtain the pre-enhanced speech. To achieve a further level of enhancement, an IKF is next applied to the pre-enhanced speech. An improved method based on Curvelet Transform using different window functions is presented for the speech enhancement. The window function is used for pre-processing of speech signals. In this method, instead of using two-dimensional (2-D) discrete Fourier Transform, Curvelet transform is employed with spectral magnitude subtraction method. the proposed method is evaluated under various noise conditions. Experimental results are provided to demonstrate the effectiveness of the proposed method as compared to some previous works in terms of segmental SNR and perceptual evaluation of speech quality (PESQ) as two well-known performance indexes.

Node Iocalization enabled wireless sensor network has gained immense popularity in real time due to its faster execution, high coverage area, performance and connectivity. It can achieve the primary objectives such as high connectivity and coverage area in wireless sensor networks. To completely exploit the wireless sensor networks, it is very essential to achieve a high connectivity between sensor nodes and gateways of sensor networks. Therefore, here, we have introduced a novel Local Isolated Node Localization in Wireless Sensor Networks based on probability analysis to locate the isolate node probability precisely, enhance connectivity between nodes and improve coverage area and scalability. A local collaborative pair method is introduced for isolated node recognition and ensures high connectivity. Experimental results verifies superiority of our proposed Isolated Node Localization model in terms of distance between sensor nodes, high connectivity and coverage area, identification of isolated sensor node location when networks are coinciding with each other at the boundaries and it also consider channel randomness while searching for connectivity between nodes.

The remote sensing image technology is growing for the satellite communications. Due to huge size of the satellite image data, there is an overhead in terms of storage capacity, power consumption for the transmission so this is the major challenge in this field. To overcome these issues in this work we have proposed lifting scheme based image compression. The proposed architecture is multiplier-less, so the computational complexity is reduced by using this method. Results show that the power consumption is less for this method; it gives the better operating frequency and better reconstruction quality of image. The work is implemented using reconfigurable architecture using FPGA.

Melanoma is one of the deadliest cancer to be treated as well to detect in initial phase. Here we take the skin lesion by ROI and then we take out features of it then it needs to be segmented whether the particular image is cancerous or not. If it is cancerous then classify the extracted features and discuss about type of stages. A novel 3D reconstruction algorithm from 2D dermoscopic images is proposed. The detection of 3D image shape and RGB are to be carried out. In this paper we have proposed this work for 3D depth parameter which will enhance the classification rate.

Over the last few decades mean communication range has attracted considerable attention in wireless networks. One of the main metric for deciding the performance of a wireless network is the mean communication. The analysis of fading effect on mean communication range is equally important for establishing a reliable and efficient communication system. In this research paper, the effect of Nakagami fading on mean communication range in case of wireless sensor networks has been discussed. Extensive investigations are conducted to analyse the effect of Nakagami-m fading to signify importance of it over the mean communication range. The results are governed and enhanced through the efficient use of simulation tools.

Node isolation is one of the fundamental metrics in the design consideration and evaluation of wireless ad hoc network. This paper is aimed to introduce a statistical framework for the computing of the isolation probability of a randomly chosen node in a wireless network. The statistical framework is proposed in the context of lognormal shadowing on Nakagami fading for multiple inputs multiple output schemes. In this work the focus is on path loss component, network topology, node density and performance of a node. The performance of connectivity between nodes in a dense network are analysed by deriving analytical models. Analysis of experimental results indicate that they are useful in estimating connectivity issues and implementing more secure wireless ad hoc networks.