456 results about "Error feedback" patented technology

An articulated instrument is controllably movable between areas of different work space limits, such as when it is extendable out of and retractable into a guide tube. To avoid abrupt transitions in joint actuations as the joint moves between areas of different work space limits, a controller limits error feedback used to control its movement. To provide smooth joint control as the instrument moves between areas of different work space limits, the controller imposes barrier and ratcheting constraints on each directly actuatable joint of the instrument when the joint is commanded to cross between areas of different work space limits.

Stable, robust, and high-resolution delta-sigma error feedback modulators, such as those used in digital-to-analog converters and phase-locked loops, include an L-order noise transfer function that is provided with L+1 high-order bits from a truncation element. The stability of such delta-sigma error feedback modulators is independent of the input signal. Moreover, the out-of-band gain of the noise transfer function need not be limited, which improves the resolution and the signal-to-noise ratio of the in-band signal.

A analog-to-digital converters and second order noise shaping systems are presented for providing a noise shaped analog feedback signal to a A / D converter in an analog-to-digital conversion system. The noise shaping system comprises a first order integrator having a single amplifier, and a digital error feedback system comprising a digital signal processing system, in which the digital error feedback system provides an analog feedback signal to the A / D converter with second order noise shaping with respect to a quantization error associated with the A / D converter.

The invention relates to a calcination predictive control method and a calcination predictive control system for a rotary cement kiln. The method comprises the following steps of: (1) acquiring field data of the calcining process of the rotary cement kiln and classifying the field data; (2) respectively carrying out model identification on the data and organically combining the data to establish a prediction model; (3) carrying out prediction on historical and future data information on the calcining process by the prediction model to obtain an output of the calcining process and outputting error feedback correction by utilizing the model to obtain a closed-loop prediction output of the calcining process; and (4) according to the closed-loop prediction output and a reference output trace,constructing a non-linear target function and carrying out solution of a optimal solution on the target function by using a sequential quadratic programming method to obtain a predicted value of the calcination controlling quantity. The system comprises an intelligent detection instrument and an actuator which are connected with the rotary cement kiln, a data storage device and an upper computer,wherein a calcination predictive control algorithm is embedded in the upper computer. The calcination predictive control method and the calcination predictive control system for the rotary cement kiln can be suitable for the dynamism of the calcining process of the rotary cement kiln and the coupling, nonlinearity and obsoleteness between multiple variables, and obtain good control effect.

The invention belongs to the technical field of natural language processing text classification, in particular to a multi-source multi-label text classification method based on an improved seq2seq model and a system thereof. The method comprises the following steps: data input and pretreatment, word embedding, encoding, encoding and splicing, decoding, model optimization and prediction output. Themethod of the invention has the following beneficial effects: adopting a seq2seq depth learning framework, constructing a plurality of encoders, and combining the attention mechanism to be used for atext classification task, so as to maximize the use of multi-source corpus information and improve the classification accuracy of the multi-label; In the error feedback process of decoding step, according to the characteristics of multi-label text, an intervention mechanism is added to avoid the influence of label sorting, which is more in line with the essence of multi-label classification problem. The encoder adopts the circulating neural network, which can learn according to the time step effectively. The decoding layer adopts one-way loop neural network and adds attention mechanism to highlight the learning focus.