Prior art

Résumé

Prior art (also known as state of the art or background art) is a concept in patent law used to determine the patentability of an invention, in particular whether an invention meets the novelty and the inventive step or non-obviousness criteria for patentability. In most systems of patent law, prior art is generally defined as anything that is made available, or disclosed, to the public that might be relevant to a patent's claim before the effective filing date of a patent application for an invention. However, notable differences exist in how prior art is specifically defined under different national, regional, and international patent systems. The prior art is evaluated by patent offices as part of the patent granting process in what is called “substantive examination” of a patent application in order to determine whether an invention claimed in the patent application meets the novelty and inventive step or non-obviousness criteria for patentability. It may also be considered by pat

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https://en.wikipedia.org/wiki/Prior_art

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Technology In-Sourcing and the Creation of Pioneering Technologies

Vareska van de Vrande

This study analyzes the effect of different external technology sourcing modes on the creation of radical innovation in companies. Moreover, since prior research has indicated that exploration consists of looking beyond both organizational and technological boundaries, the role of technological distance between the partnering firms and the role of technological newness are also included. In particular, this paper examines how they affect the relationship between external technology sourcing and the creation of pioneering technologies (technologies that do not build on any existing technologies), which are used as a proxy for radical innovations. Using a sample of companies that were from the pharmaceutical industry, the results indicate that strategic alliances and corporate venture capital investments have a positive effect on the creation of pioneering technologies, whereas the effect of M&As is found to be negative. Additionally, the results show that the impact of these governance modes on the creation of pioneering technology is indeed affected by the newness of the technology and relatedness of the technological portfolios of the partnering firms. A larger technological distance between the two partnering firms increases the effect of strategic alliances on the creation of pioneering technologies. In addition, the results indicate that technological newness weakens the positive effect of CVC investments and non-equity alliances on the creation of pioneering technologies.

2011

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Design of an Always-On Deep Neural Network-Based 1-mu W Voice Activity Detector Aided With a Customized Software Model for Analog Feature Extraction

Minhao Yang

This paper presents an ultra-low-power voice activity detector (VAD). It uses analog signal processing for acoustic feature extraction (AFE) directly on the microphone output, approximate event-driven analog-to-digital conversion (ED-ADC), and digital deep neural network (DNN) for speech/non-speech classification. New circuits, including the low-noise amplifier, bandpass filter, and full-wave rectifier contribute to the more than 9x normalized power/channel reduction in the feature extraction front-end compared to the best prior art. The digital DNN is a three-hidden-layer binarized multilayer perceptron (MLP) with a 2-neuron output layer and a 48-neuron input layer that receives parallel event streams from the ED-ADCs. To obtain the DNN weights via off-line training, a customized front-end model written in python is constructed to accelerate feature generation in software emulation, and the model parameters are extracted from Spectre simulations. The chip, fabricated in 0.18-mu m CMOS, has a core area of 1.66 x 1.52 mm(2) and consumes 1 mu W. The classification measurements using the 1-hour 10-dB signal-to-noise ratio audio with restaurant background noise show a mean speech/non-speech hit rate of 84.4%/85.4% with a 1.88%/4.65% 1-sigma variation across ten dies that are all loaded with the same weights.

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2019

Chargement

Modern wireless communication systems require efficient channel equalizer implementations. This paper explores the design space of reduced-state sequence estimation (RSSE). We show how the concept of pre-computation can be applied to greatly reduce computational complexity, such that efficient RSSE architectures can be derived. As a proof of concept, an RSSE was implemented in dedicated hardware, that achieves a 1.6 times higher hardware efficiency when compared to prior art.

IEEE2013

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