The numerical controlled oscillator has wide application in radar, digital receiver, and software radio system. Firstly, this paper introduces the traditional CORDIC algorithm. Then in order to improve computing speed and save resources, this paper proposes a kind of hybrid CORDIC algorithm based on phase rotation estimation applied in numerical controlled oscillator (NCO). Through estimating the direction of part phase rotation, the algorithm reduces part phase rotation and add-subtract unit, so that it decreases delay. Furthermore, the paper simulates and implements the numerical controlled oscillator by Quartus II software and Modelsim software. Finally, simulation results indicate that the improvement over traditional CORDIC algorithm is achieved in terms of ease of computation, resource utilization, and computing speed/delay while maintaining the precision. It is suitable for high speed and precision digital modulation and demodulation.
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http://dx.doi.org/10.1155/2014/897381 | DOI Listing |
Sensors (Basel)
July 2024
School of Integrated Circuits, Peking University, Beijing 100871, China.
Electrocardiography (ECG) has emerged as a ubiquitous diagnostic tool for the identification and characterization of diverse cardiovascular pathologies. Wearable health monitoring devices, equipped with on-device biomedical artificial intelligence (AI) processors, have revolutionized the acquisition, analysis, and interpretation of ECG data. However, these systems necessitate AI processors that exhibit flexible configuration, facilitate portability, and demonstrate optimal performance in terms of power consumption and latency for the realization of various functionalities.
View Article and Find Full Text PDFSci Rep
February 2024
Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, Iran.
Spiking networks, as the third generation of neural networks, are of great interest today due to their low power consumption in cognitive processes. This important characteristic has caused the hardware implementation techniques of spiking networks in the form of neuromorphic systems attract a lot of attention. For the first time, the focus is on the digital implementation based on CORDIC approximation of the Hindmarsh-Rose (HR) neuron so that the hardware implementation cost is lower than previous studies.
View Article and Find Full Text PDFSci Rep
February 2024
Faculty of Electrical Engineering, Shahid Beheshti University, Tehran, 1983969411, Iran.
The paramount concern of highly accurate energy-efficient computing in machines with significant cognitive capabilities aims to enhance the accuracy and efficiency of bio-inspired Spiking Neural Networks (SNNs). This paper addresses this main objective by introducing a novel spatial power spike-timing-dependent plasticity (Spatial-Pow-STDP) learning rule as a digital block with high accuracy in a bio-inspired SNN model. Motivated by the demand for precise and accelerated computation that reduces high-cost resources in neural network applications, this paper presents a methodology based on COordinate Rotation DIgital Computer (CORDIC) definitions.
View Article and Find Full Text PDFWe propose a simple but high-performance trigonometric-memory-polynomial decision-feedback equalizer (TMP-DFE) to cope with the nonlinear distortions in intensity-modulation direct-detection (IM/DD) systems. The proposed method employs sine and cosine operations of received samples, which can be implemented by the efficient CORDIC algorithm using only additions and shifts, to fit odd- and even-order nonlinearities with the effect of different nonlinear orders adjusted by the nonlinear factor. We further propose TMP improved-weighted DFE (TMP-IWDFE) to reduce the error propagation probability of decision feedback.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2023
Hand movement recognition using Electromyography (EMG) signals have gained much significance lately and is extensively used for rehabilitation and prosthetic applications including stroke-driven disability and other neuromuscular disorders. Herein, quantitative analysis of EMG signals is very crucial. However, such applications are constrained by power consumption limitations due to the battery backup necessitating low-complex system design and the on-chip area requirement.
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