Thank you very much for downloading table of integrals series and products. Maybe you have knowledge that, people have look hundreds times for their chosen books like this table of integrals series and products, but end up in harmful downloads. Rather than reading a good book with a cup of coffee in the afternoon, instead they cope with some harmful virus inside their laptop. table of integrals series and products is available in our book collection an online access to it is set as public so you can get it instantly. Our book servers saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the table of integrals series and products is universally compatible with any devices to read.

Table Of Integrals Series And Products

Hybrid PSO-GSA for energy efficient spectrum sensing in cognitive radio network

Summary
The design of monitoring systems for marine areas has increased in the last years One of the many advantages of wireless sensor networks is the quick process in data acquisition The information from sensors can be processed, stored, and transmitted using protocols efficiently designed to energy saving and establishing the fastest routes The processing and storing of data can be very useful for taking intelligent decisions for improving the water quality The monitoring of water exchange in aquaculture tanks is very important to monitor the fish welfare Thus, this paper presents the design, deployment, and test of a smart data gathering system for monitoring several parameters in aquaculture tanks using a wireless sensor network The system based on a server is able to request and collect data from several nodes and store them in a database This information can be postprocessed to take efficient decisions The paper also presents the design of a conductivity sensor and a level sensor These sensors are installed in several aquaculture tanks The system was implemented using Flyport modules Finally, the data gathering system was tested in terms of consumed bandwidth and the delay Transmission Control Protocol (TCP) packets delivering data from the sensors

/pdf/design-and-deployment-of-a-smart-system-for-data-gathering-26k5pcyrab.pdf

Design and deployment of a smart system for data gathering in aquaculture tanks using wireless sensor networks

A cooperative cognitive radio network (CRN) with improved energy detection-based spectrum sensing is analyzed in various fading scenarios. Generalized multipath (Nakagami- $m$ ) fading and enriched multipath (Nakagami- $q$ ) fading models are considered along with two other general fading distributions, i.e., $\kappa$ - $\mu$ and $\eta$ - $\mu$ distributions. For spectrum sensing, instead of conventional power 2-based detection method, the arbitrary power $p$ -based improved energy detector is used. The impact of the cognitive user mobility on the performance of the improved energy detector is investigated. Specifically, the statistics for the received signal are derived over various fading environments. The performance of the considered CRN system is evaluated in terms of probability of false alarm, probability of missed detection, and receiver operating characteristics (ROC) curves. Moreover, the area under the ROC curve is also obtained. Simulation results are provided to corroborate the theoretical results derived in this paper.

An Improved Energy Detector for Mobile Cognitive Users Over Generalized Fading Channels

In this paper, a novel prediction based cooperative spectrum sensing scheme is investigated on the performance of an energy harvesting cognitive radio (CR) network. The spectrum sensing scheme is redesigned to protect the quality of service (QoS) of primary user (PU) and to improve the utilization of spectrum holes. The decision about the PU spectrum status and energy harvesting (RF and non-RF) of a CR node are based on prediction as well as sensing at individual CR level. We consider simultaneous spectrum sensing and energy harvesting scenario through the incorporation of an energy splitting device. A CR harvests from non-RF resources if both the decisions (decision of prediction and decision of spectrum sensing) do not match or if both the decisions match in favor of the absence of PU. On contrary, it harvests from RF resources while both the decisions match in favor of the presence of PU. A CR node transmits only if both decisions indicate the absence of PU. A CR user opportunistically uses the PU spectrum for its transmission purpose under a collision constraint. The collision constraint gives an extra protection to the QoS of PU on rearrival of PU. Novel analytical expressions for detection performance, harvested energy, and network throughput are developed. The impact of prediction and other network parameters such as number of detection frames, number of cooperative CR user, splitting parameter, collision probability on throughput performance is investigated. Improvement in spectrum reuse and energy penalty during harvesting is indicated. Impact of noise power estimation on the sensing performance is also studied.

Throughput of an Energy Harvesting Cognitive Radio Network Based on Prediction of Primary User

In this project, we aim to classify the speech taken as one of the four emotions namely, sadness, anger, fear and happiness. The samples that have been taken to complete this project are taken from Linguistic Data Consortium (LDC) and UGA database. The important characteristics determined from the samples are energy, pitch, MFCC coefficients, LPCC coefficients and speaker rate. The classifier used to classify these emotional states is Support Vector Machine (SVM) and this is done using two classification strategies: One against All (OAA) and Gender Dependent Classification. Furthermore, a comparative analysis has been conducted between the two and LPCC and MFCC algorithms as well.

Speech Emotion Recognition using Support Vector Machine.

In this paper, the performance of cooperative spectrum sensing (CSS) with censoring of cognitive radios (CRs) has been evaluated using a simple majority logic fusion in presence of Rayleigh fading affecting both the sensing (S) and reporting (R) channels. Each CR senses the primary user (PU) using a double threshold based energy detection over the sensing channel. Censoring of CRs is done on the basis of the quality of Rayleigh faded R-channel. Typically two types of censoring such as rank-based and threshold-based censoring are considered to select the best CR based on the quality of the R-channels between CRs and a fusion center (FC). The performance of CSS, in terms of average missed detection, is evaluated in terms of relevant network parameters such as; (i) number of selected CRs, (ii) censoring thresholds, (iii) fail sensing probabilities, (iv) S and R-channel signal to noise ratios (SNRs) under both the perfect and imperfect channel estimation. The performance in terms of agility gain, normalized average number of transmitted bits for different number of CRs is also studied. Further the performance of double threshold based energy detection is compared with that of single threshold based energy detection. Our studies demonstrate that censoring with double threshold outperforms the censoring with single threshold.

Spectrum sensing with censoring of double threshold based cognitive radios in Rayleigh fading

Summary
Spectrum sensing in cognitive radio networks imposes some security threats to the secondary users (SUs) such as primary user emulation attack (PUEA). In the present paper, throughput of an SU is studied for cognitive radio network under PUEA where SU spectrum access is hybrid, ie, either in overlay mode or in underlay mode. A novel analytical expression for throughput of an SU in presence of PUEA is developed. Impact of several parameters such as sensing time, attacker strength, attacker's presence probabilities, maximum allowable SU transmit power, and tolerable interference limit at primary user on the throughput of an SU is investigated. The throughput performance under PUEA and without PUEA is compared.

Throughput performance under primary user emulation attack in cognitive radio networks

This paper proposes a novel cooperative spectrum sensing network (CSSN) with improved energy detector (IED) based cognitive radio (CR) users. Every CR user is furnished with multiple antennas (M) and performs itself selection combining (SC) operation. All the CRs sense a primary user (PU) via erroneous sensing channels (S) and send the data to a fusion center (FC) via erroneous reporting channels (R). At FC, decision about PU is evaluated with the assistance of k-out-of-N rule. Detection probability expressions for a CR and FC subject to noise plus Rayleigh/Rician fading are developed. Also both simulation and analytical frameworks for throughput analysis are presented. The analytical performance results are also validated using simulation performance results. Performance comparisons between IED and conventional energy detectors (CED) are presented in terms of throughput and total error rate for several parameter values. Further, overall performance of throughput and total error rate in Rayleigh/Rician fading channels is investigated. The joint effects of diversity and fading on the CSSN throughput is also additionally discussed. Channel error (r) impact on the throughput and total error performances for each proposed and traditional networks is studied. Optimization of several parameters for maximizing the throughput and minimizing the total error is also studied. Throughput overall performance of proposed CSSN is plenty better than the conventional network in each fading channel. For several values of M and r, $$p_{\mathrm{{opt}}}$$
 , $$\lambda _{\mathrm{{n, opt}}}$$
 and $$N_{\mathrm{{opt}}}$$
 values are calculated subject to each fading environment. Both analytical and MATLAB simulation results are matched. Under imperfect channel conditions, performances in terms of throughput and total error are not up to the mark but significant performance improvement has been obtained with diversity at each CR level.

Abhijit Bhowmick

Papers

Speech Emotion Recognition using Support Vector Machine.

Spectrum sensing with censoring of double threshold based cognitive radios in Rayleigh fading

Throughput performance under primary user emulation attack in cognitive radio networks

Throughput performance of cooperative spectrum sensing network with improved energy detectors and SC diversity over fading channels

Analysis of energy-efficient cooperative spectrum sensing with improved energy detectors and multiple antennas over Nakagami-q/n fading channels