This paper presents the design of a switched-current (SI) Double-Integrator Sigma-Delta Modulator (DISDM) for A/D conversion that is intended for voice-band (4kHz) telecommunication applications. With the creation of ...
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General quadratic detectors are defined and linked to the discrete-time version of Teager's model [1], to quadratic (also known as bilinear) time-frequency representations [3] and to other theory. As demonstrated ...
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The effective number of bits of a linear Analog-to-Digital Converter (ADC) can be computed using the code density histogram method. In this article, the technique is adapted to test an oversampling or Sigma-Delta (Σ...
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Presents two different methodologies for built-in self-diagnostic of boards and systems by space-time compression of test responses. The first method, soft decision, uses nonbinary multiple error-correcting codes to o...
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The authors present the design of a switched-current (SI) double-integrator sigma-delta modulator (DISDM) for analog-to-digital (A/D) conversion that is intended for voiceband (4-kHz) telecommunication applications. W...
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The authors present the design of a switched-current (SI) double-integrator sigma-delta modulator (DISDM) for analog-to-digital (A/D) conversion that is intended for voiceband (4-kHz) telecommunication applications. With the creation of several new SI signal processing building blocks, a SI DISDM has been designed and laid out in Northern Telecom's 1.2- mu m CMOS process having an area of 0.5 mm/sup 2/ and a predicted power consumption of 2.5 mW. Transistor-level simulation (SPICE) of the SI DISDM design shows that the circuit performs reasonably well, rating it at 12 b of linear resolution. In comparison with corresponding switched-capacitor DISDM designs, the SI version provides a dramatic reduction in both power and area requirements; but, more importantly, the SI design does not utilize linear capacitors and can be fabricated using a standard digital CMOS process.< >
The effective number of bits of a linear analog-to-digital converter (ADC) can be computed using the code density histogram method. The technique is adapted to test an oversampling or sigma-delta ( Sigma Delta ) conve...
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The effective number of bits of a linear analog-to-digital converter (ADC) can be computed using the code density histogram method. The technique is adapted to test an oversampling or sigma-delta ( Sigma Delta ) converter. It is assumed that the device under test includes a Sigma Delta modulator, a decimator, and a mu -law compressor. The analog stimulus to the device under test is supplied by a precision signal generator, and the code density histogram of the 8-b mu -law compressed output of the ADC is analyzed to determine whether the converter is performing within its specifications. Simulation results which were obtained using a very simple model for the ADC and additive white Gaussian noise are presented.< >
General quadratic detectors are defined and linked to the discrete-time version of Teager's model (1980), to quadratic (also known as bilinear) time-frequency representations, and to other theory. As demonstrated ...
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General quadratic detectors are defined and linked to the discrete-time version of Teager's model (1980), to quadratic (also known as bilinear) time-frequency representations, and to other theory. As demonstrated on speech, these detectors have resolution advantages in simultaneous frequency selectivity and temporal resolution over linear detectors. Preprocessing for pitch detection using the detector is investigated, and it is shown that fast preprocessing for pitch tracking can be obtained by a suitable choice of coefficients. Simple speaker-independent phoneme classification based on a quadratic preprocessor and an artificial neural network is also examined, and comparative results indicate that a quadratic preprocessor facilitates the accurate estimation of waveform features. The preliminary results also suggest that these waveform features may provide useful information for fine phonetic distinctions.< >
The principle of minimum cross entropy (MCE) is used to generate positive distributions in the Cohen-Posch (1985) class of proper time-frequency distributions (TFDs). The MCE-TFDs are not only intuitively satisfying, ...
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The principle of minimum cross entropy (MCE) is used to generate positive distributions in the Cohen-Posch (1985) class of proper time-frequency distributions (TFDs). The MCE-TFDs are not only intuitively satisfying, but they also yield the correct marginals, have strong finite support, and are everywhere nonnegative. The usual cross-term artifacts that hinder interpretation of other time-frequency representations (most notably, the Wigner-Ville) are not a problem with the MCE-TFDs. Examples of speech and chirps are given and compared to the spectrogram. An interesting observation in the case of speech is that spectrograms more closely resemble time-conditional-frequency distributions (narrowband) or frequency-conditional-time distributions (wideband) than they do joint time-frequency distributions.< >
A framework, based on nonbinary multiple error correcting codes, for built-in self-diagnostics is presented. Novel space-time compressors are proposed for test response compression and fault diagnosis. Fault-detecting...
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A framework, based on nonbinary multiple error correcting codes, for built-in self-diagnostics is presented. Novel space-time compressors are proposed for test response compression and fault diagnosis. Fault-detecting and locating capabilities for space-time compressors are analyzed in the case when nonbinary Reed-Solomon codes are used. Fault-masking and diagnosis probabilities for the chip-independent error model are estimated. For this error-model, the fault-masking probabilities are analyzed using the weight distributions of Reed-Solomon codes.< >
Presents two different methodologies for built-in self-diagnostic of boards and systems by space-time compression of test responses. The first method, soft decision, uses nonbinary multiple error-correcting codes to o...
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Presents two different methodologies for built-in self-diagnostic of boards and systems by space-time compression of test responses. The first method, soft decision, uses nonbinary multiple error-correcting codes to obtain space-time signatures. These obtained signatures and the corresponding precomputed references are compared and magnitudes of distortions in signatures are analyzed to identify faulty components. The second method, hard decision, makes use of the information indicating whether the corresponding signatures are distorted or not. Both approaches show considerable savings in hardware overheads when compared with a straightforward approach where a separate signature is required for every component. A transition from the soft to hard decision approach results in an increase in the number of signatures required for diagnostic but at the same time it results in a decrease in the complexity of a fault locating algorithm. Results pertaining to VLSI implementations are presented where the hardware overhead is estimated in terms of two-input equivalent gates.< >
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