3results about How to "Balanced weight" patented technology

A kind of dual-phase variable loop order increment high-resolution analog-digital converter circuit based on multi-bit quantization, containing analog loop filter (hereinafter referred to as ΔΣ loop) and downsampling digital filter, there is phase switching switch, the phase switching switch includes L-1 phase switching switch in loop filter and L-1 phase switching switch in downsampling digital filter.The present application uses the architecture of first order and high order IADC mixedly, signal weight is made uniform by distributing the period number of phase 1 larger in total clock cycle, while fast accumulation is obtained by high order accumulation in a small part of total clock cycle to effectively improve the accuracy of system.Guarantee the weight of part input signal uniform in a sampling conversion period, to improve the effectiveness of DWA to suppress multi-bit DAC nonlinearity.

The application discloses a wireless smoke sensing device battery power prediction method and system based on deep learning, belongs to the technical field of time series prediction, extracts the smoke concentration detection value, the daily fire alarm message reporting frequency and the total number of fire alarm message reporting since the installation of the device from each device as three features related to the battery power of the smoke sensing device, combines the air temperature, the wind speed, the humidity and the local features of the device itself on the same day to arrange the features into time series, divides the time series into time series with days as the unit by using a sliding window, adds a plurality of buffer vectors at the beginning of the time series, inputs the buffer vectors into an improved self-attention model, introduces a self-attention mechanism using the buffer vectors, and outputs the prediction result of the battery power. The improved self-attention algorithm is used to make the output weight more balanced, improve the accuracy of the battery power prediction, and can also predict the battery power in real time, update the model regularly, and improve the stability and timeliness of the model.

The utility model provides an adjusting structure for a winding machine, which comprises a base, fixing plates are arranged on two sides of the base, connecting shafts are respectively and rotatably arranged on the two fixing plates, connecting cylinders, vertical plates I and adjusting screw rods are respectively and slidably arranged on the two connecting shafts, connecting plates I are arranged on the connecting cylinders, the connecting plates I are rotatably connected with the inner side ends of the adjusting screw rods, and the vertical plates I are rotatably connected with the inner side ends of the adjusting screw rods. The winding roller is detachably arranged between the two connecting cylinders, and limiting bolts which can abut against the connecting shafts so as to fix the connecting positions of the connecting cylinders and the connecting shafts are further connected to the connecting cylinders in a threaded mode. According to the adjusting structure for the winding machine, the basic requirement for winding a CPP thin film can be met, the axial length of the winding structure can be flexibly and continuously adjusted, and then the winding requirement for thin films with different widths is fully met.