Understanding Smart Sensors - Nomads.usp

Control Techniques 165linear-vector quantization classifier requires a similar calculation of the Euclideandistance between an unknown vector of features and a lexicon of templates.Time warping is another approach for speech recognition.Spectral processing involves a sequence of computations. The computationsinclude a weight vector, Fourier transform, conversion from real to imaginarycomponents to power, and conversion from power to decibels. The finalcalculation of the power components of the frequency spectrum is converted todecibels using a standard linear-to-logarithmic library function. The amount ofprocessing is indicative of speech and image recognition.Associative memory is used in pattern recognition applications, in whichthe network is used to associate data patterns with specific classes or categoriesit has already learned [17].The control areas discussed in this section are aimed at some of the highendcomputing requirements in sensory systems. As shown in Table 7.4, thesetechnologies are essential for many smart-sensing applications. More than oneapproach can be used to implement a solution for these complex systems.7.7.1 RISC Versus CISCThe complex instruction set computer (CISC) architecture is the establishedapproach for desktop computing and embedded control applications. AnTable 7.4Emerging Techniques for Smart Sensing ApplicationsTechniqueVoice recognitionHandwriting recognitionMultimediaDigital soundFAX/modemData storageCD-ROMVirtual realitySynthesized speechData compressionPattern recognitionEnabling TechnologyDSP, neural network (NN), RISC, multiprocessing (MP)DSP, MP, NN, fuzzy logic (FL)DSP, FL, RISC, MPDSPRadio frequency integrated circuits (RFICs), CISCFlash, DRAM, SRAMCISCDSP, RISC, FL, MPDSP, RISC, NN, MPDSPDSP, high-performance MCU, NN