A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2005; you can also visit the original URL.
The file type is application/pdf.
Filters
A hybrid DBNS processor for DSP computation
ISCAS'99. Proceedings of the 1999 IEEE International Symposium on Circuits and Systems VLSI (Cat. No.99CH36349)
Preserved Fulltext
The modification proposed in this paper, targeted to DSP inner product computations, uses a single digit representation for the coefficient vector and a 2-digit representation for the data vector. ...
This paper introduces a modification to an index calculus representation for the Double-Base Number System (DBNS). ...
A HYBRID 2-DIGIT PROCESSOR A diagram of the hybrid processor is shown in Figure 6 . ...
doi:10.1109/iscas.1999.777792
dblp:conf/iscas/JullienDLMLA99
fatcat:6qm5npmhlfcjdntzzzf4j7xsgm
Comparative Study and Analysis of Performances among RNS, DBNS, TBNS and MNS for DSP Applications
2015
Journal of Signal and Information Processing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
System (TBNS) and Mixed Number System (MNS) for DSP applications. ...
This paper presents a comparative study of the performances of arithmetic units, based on different number systems like Residue Number System (RNS), Double Base Number System (DBNS), Triple Base Number ...
For real time applications and DSP related problems fast arithmetic units particularly adders and multipliers are required for enhanced performance of the processors. ...
doi:10.4236/jsip.2015.62005
fatcat:4ecql6qofzgtlonqy64mxexqzu
Embedded Mission Decision-Making based on Dynamic Decision Networks in SoPC Platform
2019
International Journal of Advanced Computer Science and Applications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The proposed approach is then validated with a practical case UAV mission planning using the proposed dynamic decision-maker implemented on embedded system based on a hybrid device. ...
After proposing a DBN model, a probabilistic approach based on Multiple-Criteria Decision-Making (MCDM) is then applied to find the best configuration reaching a balance between performance and energy ...
Digital signal processors (DSP) or FPGAs are used for hardware implementation of such real-time systems. ...
doi:10.14569/ijacsa.2019.0101287
fatcat:zqg3wnaun5fubgsy3nkcrz6u4m
Wireless Channel Scene Recognition Method Based on an Autocorrelation Function and Deep Learning
2020
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The tested wireless channel data were imported into the computer processor to verify the recognition effect of the proposed method. ...
Following a similar derivation, the DSP can be theoretically obtained for other kinds for Rayleigh time-varying channels. ...
doi:10.1109/access.2020.3044167
fatcat:uwik7iub5bbkbeqxdlqfijvvk4
Hardware implementation of spiking neural networks on FPGA
2020
Tsinghua Science and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
It features a hybrid updating algorithm, which combines the advantages of existing algorithms to simplify hardware design and improve performance. ...
His current research interests include embedded systems, parallel computing, multicore design, and system-on-achip. Weimin Zheng received the MS degree ...
Acknowledgment This work was supported in part by the Beijing Innovation Center for Future Chip, Tsinghua University, in part by the Science and Technology Innovation Special Zone project, China, and in ...
doi:10.26599/tst.2019.9010019
fatcat:daag6qtcrfh2xklrtbj3nxlmda
Robustness of hardware-oriented restricted Boltzmann machines in deep belief networks for reliable processing
2016
Nonlinear Theory and Its Applications IEICE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
RBMs used in deep belief networks (DBNs) demonstrate robustness against memory errors during and after learning. ...
Fine-tuning has a significant impact on the recovery of accuracy under the presence of static errors that may modify structural data of RBMs. ...
Muraoka of Toshiba Corporation for their invaluable support and suggestions. ...
doi:10.1587/nolta.7.395
fatcat:hde3rpci2fbdlpczgahdrh7fze
Eye State Identification Utilizing EEG Signals: A Combined Method Using Self-Organizing Map and Deep Belief Network
2022
Scientific Programming
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
This paper accordingly proposes a new method for EEG signal analysis through Self-Organizing Map (SOM) clustering and Deep Belief Network (DBN) approaches to efficiently improve the computation and accuracy ...
The method is developed using SOM clustering and DBN, which is a deep layer neural network with multiple layers of Restricted Boltzmann Machines (RBMs). ...
In fact, a hybrid intelligent method is developed through Self-Organizing Map (SOM) clustering and Deep Belief Network (DBN) approaches. ...
doi:10.1155/2022/4439189
fatcat:3hvwxfryzzaftjz4ap6zip7u2q
Speech recognition using deep neural network - recent trends
2017
International Journal of Intelligent Systems Design and Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
She serves as a reviewer to several journals and IEEE international and national conferences. Her areas of interest include speech recognition, soft-computation and HCI applications. ...
ANNs with deep learning which uses a generative, layer by-layer pre-training method for initialising the weights has provided best solution for acoustic modelling for speech recognition. ...
The use of a 'bottleneck' in the last layer of the BP-DBN proved to help avoid over fitting while hybrid generative and discriminative training prevent over fitting in the AM-DBN. ...
doi:10.1504/ijisdc.2017.082853
fatcat:74c7x6rognayjpbuverpumox54
A Review on Driver Face Monitoring Systems for Fatigue and Distraction Detection
2014
International Journal of Advanced Science and Technology
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Although a precise definition for fatigue is not presented yet, but there is a relation between the fatigue/drowsiness and body temperature, electrical skin resistance, eye movement, breathing rate, heart ...
A precise and scientific definition for fatigue has not been presented yet; therefore, there is not any quantitative criterion to measure it. ...
DSP and FPGA are flexible to programming via software and hardware respectively. Therefore, in the driver face monitoring systems, DSP or FPGA is often used as processor. ...
doi:10.14257/ijast.2014.64.07
fatcat:wqzph4nohrcifgh4lknbsqov4y
From DNNs to GANs: Review of efficient hardware architectures for deep learning
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Similarly, different algorithms have been adapted to design a DSP processor compatible for fast performance in neural network, activation function, convolutional neural network and generative adversarial ...
Presently available DSP processors are incapable of performing these operations and they mostly face the problems, for example, memory overhead, performance drop and compromised accuracy. ...
This paper primarily focused on DBN, hence for activation function, a novel tanh design is proposed using finite-state-machine. ...
arXiv:2107.00092v1
fatcat:i6kijx7pavdajeskn4lip7gnhe
Harmonic Detection Technology for Power Grids Based on Adaptive Ensemble Empirical Mode Decomposition
2021
IEEE Access
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
For such cases, the development of deep neural networks has provided a new solution for harmonic detection. ...
Ensemble empirical mode decomposition (EEMD) provides a new approach for harmonic detection in power systems. ...
Then, an adaptive deep neural network model based on a deep belief network (DBN) structure with a backpropagation (BP) layer (DBN-BP) can be trained and used to set the white noise parameters for EEMD ...
doi:10.1109/access.2021.3055553
fatcat:ldfnhgffrve35fw3v3ltv2imha
Accelerating Deep Neural Networks implementation: A survey
2021
IET Computers & Digital Techniques
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Deploying such Deep Neural Networks (DNN) on embedded devices is still a challenging task considering the massive requirement of computation and storage. ...
Field Programmable Gate Arrays (FPGAs) are promising platforms for the deployment of large-scale DNN which seek to reach a balance between the above objectives. ...
Whole systems can be integrated on a chip using many hardware components such as memories, fast devices, DSP units and processor cores which expedite the design of such large-scale systems. ...
doi:10.1049/cdt2.12016
fatcat:3kl4j5ztl5eahmgv7vetu2egay
A new binary arithmetic for finite-word-length linear controllers: MEMS applications
2014
2014 9th International Design and Test Symposium (IDT)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
The CSE problem of disappearing patterns due to colliding digits DMAC Double Multiply-And-Accumulate DSP Digital-Signal-Processor/Processing FF Flip-Flop FPGA Field Programmable Gate Array FPR Fixed-Point ...
Analog Converter DAG Directed Acyclic Graphs, a framework for solving SCM and MCM DBNS Double Base Number System, an existing number representation system DFS Dynamic Frequency Scaling Digit Clashing ...
general-purpose-processor or a DSP. ...
doi:10.1109/idt.2014.7038608
dblp:conf/idt/OudjidaLBC14
fatcat:ykr7hhrd7ndy5jbmu53hb3t7vm
Semantics Interaction Control for Constructing Intelligent Ecology of Internet of Things and Critical Component Research
2018
Journal of Computer and Communications
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
For this purpose, in this paper, first, we present a type of novel intelligent deep hybrid neural network algorithm based on a deep bidirectional recurrent neural network integrated with a deep backward ...
Intelligent equipment is a kind of device that is characterized by intelligent sensor interconnections, big data processing, new types of displays, human-machine interaction and so on for the new generation ...
The popular system architecture includes the embedded microprocessor unit (EMP), the embedded micro controller unit (MCU), embedded digital signal processors (DSP), embedded systems on chip (SOC) and so ...
doi:10.4236/jcc.2018.611003
fatcat:ryq5moawtjg3pm4pkvfjd4xmze
CNNLab: a Novel Parallel Framework for Neural Networks using GPU and FPGA-a Practical Study with Trade-off Analysis
[article]
2016
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Experimental results on the state-of-the-art Nvidia K40 GPU and Altera DE5 FPGA board demonstrate that the CNNLab can provide a universal framework with efficient support for diverse applications without ...
However, the diversity and large-scale data size have posed a significant challenge to construct a flexible and high-performance implementation of deep learning neural networks. ...
CNNLab maps the applications into computing kernels using CUDA and OpenCL programming interfaces. • CNNLab is based on a heterogeneous hybrid system which includes the software processor, GPU accelerator ...
arXiv:1606.06234v1
fatcat:en7acoahonb7beqrnxv553g46e
« Previous
Showing results 1 — 15 out of 51 results