FinFET technology, a groundbreaking leap in semiconductor design, has substantially affected the buildup of hardware for the use of artificial intelligence (AI) and machine learning (ML) applications. This study investigates the developing uses of FinFETs in AI and ML hardware, explaining their high-quality fulfillment, power efficiency, and scalability. As AI and ML algorithms demand greater computing capacity, FinFETs offer a solid answer by raising processing speed and accuracy as they lowering power consumption. This study explores numerous applications among them neuromorphic computer technology, edge AI devices, and computing performance for ML training. It also includes FinFET-based methodology case studies, demonstrating their distinct benefits over antiquated technology. Although FinFETs may have manufacturing issues and constraints, they will advance technology for ML and AI. This study emphasizes FinFET technology's crucial role in satisfying AI and ML demands, enabling further along efficient and effective hardware solutions.

In this article, a dual-port multiple inputs and multiple output (MIMO) antenna design is presented for X-band applications with computational electromagnetic simulator. The proposed MIMO antenna design is improving the performance metrics. The potential antenna has a $20\times 20\times 1.6$ mm 3 footprint. Two T-shaped patches are located on either side regarding the suggested MIMO antenna. At 8.35 GHz, the suggested antenna obtains a decent reflection coefficient. On the radiating patch, there are engraved rectangular slots. The electromagnetic tool simulates the MIMO antenna was designed. When the antenna's reflection coefficient is under −10 dB, it achieves a reflection coefficient of −33 dB. The measured and simulated parameter of proposed model antenna was presented. The wider frequency to be use for 5G communications at IoT applications of proposed MIMO antenna.

The 5G technologies and OFDM introduce a substantial element of latency in the baseband Massive MIMO system. To declaim the low delay demand of multiple input and multiple outputs, a Fast Fourier Transform (FFT) and also consequent implementation was proposed. The main idea of this proposed system is to utilize the VLSI chip routing technology and reduce computations, processing time, and low latency. This proposed system is to reduce the number of computational complexities in the downlink and reorder the uplink. In OFDM implementation, the chip area of FFTs and IFFTs is occupied by memories, and these memories can be extracted using registers or RAM. An efficient data programming approach for memories and butterflies has been developed using embedded VLSI technology with multiple inputs and outputs (MIMO), known as mass embedded MIMO systems. Using this proposed scheme (Integrated Massive MIMO), N point FFT/IFFT processor design achieves a better throughput and lowest latency than for single-input pipelined FFT or IFFT architectures. In an N-point FFT/IFFT, the introduced scheme using VLSI Technology leads to more reduction in the latency. This N-point FFT/IFFT implementation is named “Integrated Massive MIMO Systems” (IMMS).

A hybrid approach of image compression using Singular value decomposition (SVD) and Set Partition in Hierarchical Trees (SPIHT) is proposed in this paper. SVD provides less image quality with more compression rate; SPIHT offers high quality of image with more compression. In the proposed method, image is compressed using SVD and reconstructed image is given to SPIHT technique. This method is tested on MRI and X-ray images and provides an improvement in Peak Signal to Noise ratio (PSNR) of 5dB compared to SPIHT, reduced Mean Squared Error (MSE) and significant improvement in compression ratio compared to SVD and SPIHT alone

In wireless communications, the demand for wireless throughout and communication reliability as well as the user density will always increase. In this regard, one of the important technology enables for 5G network is massive MIMO technology, which is a special case of multiuser MIMO with an excess of Base Station (BS) antennas. In view of emerging networks, the energy consumption is a critical concern to meet enormous service expectations. The main limitation in this communication system is effectiveness of the spectrum utilization. To increase the effectiveness of the communication system, different techniques are to be used to increase the system throughput and decrease the power consumption. In this paper, a new less complexity suboptimal algorithm is used to separate subcarrier allocation and power distribution. An OFDM-Distributed Antenna System (DAS) is used to get more energy efficiency for Long-Term Evolution (LTE).

Automatic Recognition of horticultural items is a difficult issue that has gotten a lot of consideration during behind years because of its frequent applications in a variety of fields. Fruit Recognition is one of those difficult issues and cutting-edge, there is no strategy that gives a hearty answer for all conditions and various applications. Recognition of natural products is a regular assignment in goods, organic product fare, and import enterprises. Robotizing this system is significant in a wide extent of employments including Human Machine Interfaces(HMI) and programmed way in control structures. The recognition and classification of fruits is a key factor in harvesting operations. In this paper, a Fruit Recognition and Classification System were developed. It consists of two sections, training model of the neural network which helps to build a large database of fruit pictures and the second is called recall mode where the unknown fruit image is given to the system. Now the system will compare with the samples from the database, it also verifies the colour and texture features of the fruit. The artificial neural network are simulated in MATLAB will identify the unknown fruit which completes the process. Hence the combination of all these techniques will form a computer vision-based fruit recognition and classification system. This framework likewise fills in as a valuable apparatus in an assortment of fields, for example, business, agrarian instructive, picture recovery, and plantation science.

One of the most important advantages of the digital transmission systems for voice, data, and video communications is that they are highly reliable. But the major obstacle to higher reliability and high data transmission rate is noisy channel. By this noise, the quality of the images can be reduced and diagnosis becomes critical in case of medical images. In this paper, different test and medical images are transmitted through an channel and the noisy images are denoised by using different wavelet transform techniques (Haar, Daubechies, Coiflet, Symmlet, bi-orthogonal ). From the results it is found that the bi-orthogonal wavelet transform technique performs better in terms of the performance metrics like PSNR, MSE and SSIM compared to other wavelet transforms.

In urban and semi-urban areas, the ever increasing population is creating high raised structures and increasing tele-density. It is becoming difficult for the mobile network providers to offer quality service to the mobile user. One of the main reasons causing degradation in signal quality is multipath propagation. Because of this, the Received Signal Strength (RSS) may be either reduced or completely attenuated at the receiver. So modelling and characterisation of the channel is necessary. If there is no line-of-sight signal component from transmitting station to the receiver, then the envelop of the received signal can be statistically described by Rayleigh distribution. In this paper, real time mobile RSS in terms of power (in dBm) is recorded, analysed and its quality is tested using theoretical Rayleigh distribution and also validated using Chi-square fitness-of good test.

In highly populated urban canyons, the mobile communication signal propagate from the base station and arrives at the mobile station(or mobile phone) as a multitude of partial waves from different directions. This is known as multipath propagation. This effect gives rise to multipath fading. Due to this, received signal strength decreases and sometimes unable to recognise. So characterisation and modelling of wireless channel is important. The received signal strength in terms of power is measured using RF recorder for analysis at the mobile station at certain time intervals and the signal (in dBm) assumed to be received in multipath environment and is composed of fast fading caused by local multipath propagation and slow fading due to shadowing. In this paper, the real time mobile data is analyzed by separating fast fading components using moving average filter and then approximation of its and probability distribution functions (PDF) and cummulative distributions(CDF) are analysed.

Mobile signals propagate from base station to mobile station through space. The worst case communication channel is usually in the urban and semi-urban environments where there are many obstacles. Due to obstacles, the transmitted signal arrives at the receiver from various directions over a multiplicity of paths. Received signal strength decreases and sometimes unable to recognise. So modelling and characterisation of channel is must and highly important. Using Rayleigh distribution function characterization of attenuation and phase of a channel is done. The received signal strength in terms of power is measured using RF recorder for analysis at the mobile station at certain time intervals and the signal (in dBm) assumed to be received under homogeneous multipath conditions. In this paper the real time data is analyzed by computing its histogram (approximation of its probability distribution function, pdf) and its sample cumulative distribution function (CDF), and then verified whether the measured data fits a Rayleigh distribution using chi-square test.

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The term wireless communication refers to transfer of information via electromagnetic or acoustic waves over atmospheric space rather than along a cable. Mobile signals propagate from base station to mobile station through space. During propagation they interact with objects. Due to obstacles and reflectors, the transmitted signal arrives at the receiver from various directions over number of paths. Received signal strength decreases and sometimes unable to recognise. The received signal in terms of power is measured using RF recorder for analysis at the mobile station at certain time intervals and the signal (in dBm) assumed to be received under homogeneous multipath conditions. In this paper the real time data is analyzed by computing its histogram (approximation of its pdf) and its CDF, and then verified whether the measured data fits a Rayleigh distribution using chi-square test.

Removed.

In densely built-up areas, the transmitted signal from the base station mostly arrives at the mobile station as a multitude of partial waves from different directions. This is known as multipath propagation. This effect gives rise to multipath fading. Due to this, received signal strength decreases and sometimes unable to recognise. So characterisation and modelling of wireless channel is highly important. The received signal strength in terms of power is measured using RF recorder for analysis at the mobile station at certain time intervals and the signal (in dBm) assumed to be received in multipath environment and is composed of fast fading caused by local multipath propagation and slow fading due to shadowing. In this paper, the real time data is analyzed by separating slow fading and fast fading components using moving average filter and then individual approximation of their cumulative distribution functions (CDF) are compared with the theoretical Rayleigh distribution and lognormal distribution.