Advanced Signal Processing for Communication Networks and Industrial IoT Machines Using Low-Cost Fixed-Point Digital Signal Processor

Oyekanlu, Emmanuel; Scoles, K.; Oladele, Paul

doi:10.1109/icait.2018.8686577

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Such a promising solution will eventually minimize the requesting power consumption of the corresponding IoT applications and at the same time advance the overall computing in terms of energy efficiency. However, following conventional digital design approaches involving either specialized signal processors or more generic microcontrollers does not prove as promising as expected and especially when power consumption is highly demanded [5]. The next obvious step of utilizing a more specific-oriented CMOS-based design can be significantly enhanced with the addition of novel nanoelectronic devices with memory abilities, namely memristors, to be combined with the IoT sensors.…”

Section: Introductionmentioning

confidence: 99%

In-Memory-Computing Realization with a Photodiode/Memristor Based Vision Sensor

2021

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State-of-the-art IoT technologies request novel design solutions in edge computing, resulting in even more portable and energy-efficient hardware for in-the-field processing tasks. Vision sensors, processors, and hardware accelerators are among the most demanding IoT applications. Resistance switching (RS) two-terminal devices are suitable for resistive RAMs (RRAM), a promising technology to realize storage class memories. Furthermore, due to their memristive nature, RRAMs are appropriate candidates for in-memory computing architectures. Recently, we demonstrated a CMOS compatible silicon nitride (SiNx) MIS RS device with memristive properties. In this paper, a report on a new photodiode-based vision sensor architecture with in-memory computing capability, relying on memristive device, is disclosed. In this context, the resistance switching dynamics of our memristive device were measured and a data-fitted behavioral model was extracted. SPICE simulations were made highlighting the in-memory computing capabilities of the proposed photodiode-one memristor pixel vision sensor. Finally, an integration and manufacturing perspective was discussed.

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Section: Introductionmentioning

confidence: 99%

In-Memory-Computing Realization with a Photodiode/Memristor Based Vision Sensor

2021

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“…Instrumen tersebut dapat digunakan untuk menunjang pemahaman teori dan praktik menjadi maksimal. Beberapa aplikasi telah dilakukan menggunakan digital signal processor seperti halnya penelitian tentang penerapan Fast Fourier Transform [3], pengolahan sinyal pada jaringan komunikasi menggunakan Low Cost Fixed-Point [4], dan pengolahan sinyal terima menggunakan metode direction of arrival [5]. Ketiga penelitian tersebut menunjukkan bahwa pemanfaatan digital signal processor dapat menjadi sebuah solusi untuk meningkatkan pemahaman khususnya pada bidang sistem komunikasi.…”

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Pembangkitan Sinyal Pulse Code Modulation Berbasis OMAP-L318

Sulaeman¹,

Ashari

Rahmatullah

et al. 2020

JTERA

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Data Engineering for the Factory of the Future, Multimedia Applications and Cyber-Physical Systems

Oyekanlu

Kuhn

Mulroy

2023

Applied AI and Multimedia Technologies for Smart Manufacturing and CPS Applications

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This chapter is the companion chapter to “Part 1: State-of-the-Art Time-Series Data Formats Performance Evaluation.” In this chapter, algorithms for converting data from one format to other formats are presented. To implement the algorithms, existing open-source Python libraries are used extensively, and where needed, new Python routines for converting data formats are developed. It is envisaged that the algorithms and Python libraries and routines that are freely provided in this chapter will be useful for data engineers, data scientists, and for industrial IoT, cyber-physical systems (CPS), multimedia, and big data practitioners who are on the quest to use different types of data formats that are compatible with memory-constrained factory floor IoT devices. It will also be useful for Delta Lake and big data engineers, who are on the quest for delivering robust bronze, silver, and gold data lakes in the cloud.

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Advanced Signal Processing for Communication Networks and Industrial IoT Machines Using Low-Cost Fixed-Point Digital Signal Processor

Cited by 3 publications

References 14 publications

In-Memory-Computing Realization with a Photodiode/Memristor Based Vision Sensor

In-Memory-Computing Realization with a Photodiode/Memristor Based Vision Sensor

Pembangkitan Sinyal Pulse Code Modulation Berbasis OMAP-L318

Data Engineering for the Factory of the Future, Multimedia Applications and Cyber-Physical Systems

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