Academic literature on the topic 'Bit plan slice transform'

Structures for the evaluation of fast Fourier transforms are important components in several signal-processing applications and communication systems. Their capabilities play a key role in the performance enhancement of the whole system in which they are embedded. In this paper, a novel implementation of the discrete Fourier transform is proposed, based on a bit-slice approach and on the exploitation of the input sequence finite word length. Input samples of the sequence to be transformed are split into binary sequences and each one is Fourier transformed using only complex sums. An FPGA-based solution characterized by low latency and low power consumption is designed. Simulations have been carried out, first in the Matlab environment, then emulated in Quartus IDE with Intel. The hardware implementation of the conceived system and the test for the functional accuracy verification have been performed, adopting the DE2-115 development board from Terasic, which is equipped with the Cyclone IV EP4CE115F29C7 FPGA by Intel.

The purpose of the article is to create an effective method for low-delay monitoring of the operating state of a drill string and a drill bit without interfering with the proper drilling process. For the drilling process to be continuously controlled, an experimental setup that operates by utilizing the phase-metric method of control was developed. Any movement of the bit causes a change in the electrical characteristics of the probing signal. To obtain a stable signal from a bit immersion depth of up to 250 m, a frequency of probing electrical signals of 166 Hz and an amplitude of up to 500 V were used; the sampling rate of an analog-to-digital converter (ADC) was 10101 Hz. To identify the state of the drill string and the bit based on graphs of time-dependences of changes in the probing signal electrical characteristics, the present authors investigated a number of deep learning methods. Based on the results of the study, a series of capsular neural network methods ( CapsNet ) was chosen. The authors developed modifications of 2D-CapsNet: windowed Fourier transform (WFT) - 2D-CapsNet and frequency slice wavelet transform (FSWT) - 2D-CapsNet. Both of these methods showed a 99% accuracy in determining the transition between two layers of rocks with different properties, which is 2–3% higher than the currently used measurement-while-drilling (MWD) and logging-while-drilling (LWD) rock surveys. Both of these methods unambiguously reveal self-oscillations in the drill string. When determining a fully serviceable bit in the case of self-oscillations, the (FSWT) - 2D-CapsNet method showed an accuracy of 99%.

Reversible contrast mapping (RCM) and its various modified forms are used extensively in reversible watermarking (RW) on digital images to embed secret information. Sometimes RW demands real-time implementation that can be made by hardware realization and RCM-based RW becomes appealing due to its integer transform nature followed by least significant bit (LSB) substitution for embedding. This motivates us to propose RCM-RW on digital images with two objectives: modification on the existing RCM algorithm to increase embedding rate with low visual distortion. Later on, prototype design through field-programmable gate array (FPGA) is developed for a (256 × 256), 8-bit gray scale image using (32 × 32) image block and pipeline architecture. For a cover image of size (256 × 256), the proposed architecture requires 8,971 slices, 8,246 slice flip-flops, 9,706 numbers of four-input LUTs and 2 FIFO 16/RAMB for watermark embedding purpose. Proposed architecture consumes a power of 636[Formula: see text]mW and offers a data rate of 1.0493[Formula: see text]Mbps at an operating frequency as high as 95.3[Formula: see text]MHz.

Nowadays, in the medical world, analyzing and diagnosing acute brain stroke and its location is a difficult process. In many hospitals, however, striking symptoms with the use of computed tomography (CT) imaging for patients is an important step in screening and diagnosis. Furthermore, computer-assisted accurate detection of diseased brain regions Because of the several sorts of strokes, their uneven form, and their great intensity and size, aided design is extremely challenging. Using the bit plan slice technique and the canny detector, we created and suggested a novel approach. Our algorithm produces excellent outcomes. The results demonstrate that our proposed algorithm is an accurate and reliable technique. This study also indicates that this system can detect two different types of strokes: hemorrhagic and ischemic strokes. The results of a comparison study of our suggested technique and other methods such as negative and logarithmic transformation methods are also included in this article.