A beamforming system comprises an input module, a phase-difference module, a delay distribution module, and a delay estimation module configured to make a final delay estimation based on the delay distribution. The final delay estimation is applied to align one of two selected channels and combine the two channels to obtain a signal of interest. The phase-difference module calculates phase differences for a range of frequency bins. The delay estimation module considers all possible delays derived from the phase differences, including multiples of ±2π to overcome the ambiguity in high frequency bins when the spacing between two acoustic sensors is longer than the half of the wavelengths.

A beamforming system comprises an input module, a phase-difference module, a delay distribution module, and a delay estimation module configured to make a final delay estimation based on the delay distribution. The final delay estimation is applied to align one of two selected channels and combine the two channels to obtain a signal of interest. The phase-difference module calculates phase differences for a range of frequency bins. The delay estimation module considers all possible delays derived from the phase differences, including multiples of ±2π to overcome the ambiguity in high frequency bins when the spacing between two acoustic sensors is longer than the half of the wavelengths.

A porous composite sound-absorbing material and a method for preparing the same are provided. The porous composite sound-absorbing material includes activated carbon cotton felt, zeolite particles, and an adhesive. The activated carbon cotton felt can bond the zeolite particles to fiber surfaces thereof by means of the adhesive, so that the zeolite particles are evenly dispersed and fixed and achieve optimal sound absorption performance. Meanwhile, a large number of micro-pore structures on surfaces thereof can act synergistically with the zeolite particles, so that the porous composite sound-absorbing material has significantly better sound absorption performance than the two and has extremely high cost performance. During the preparation process, the activated carbon cotton felt after treatments, is successfully compounded with the zeolite particles with more excellent sound absorption performance, so that the sound absorption performance is significantly improved and the cost performance is extremely high.

A porous composite sound-absorbing material and a method for preparing the same are provided. The porous composite sound-absorbing material includes activated carbon cotton felt, zeolite particles, and an adhesive. The activated carbon cotton felt can bond the zeolite particles to fiber surfaces thereof by means of the adhesive, so that the zeolite particles are evenly dispersed and fixed and achieve optimal sound absorption performance. Meanwhile, a large number of micro-pore structures on surfaces thereof can act synergistically with the zeolite particles, so that the porous composite sound-absorbing material has significantly better sound absorption performance than the two and has extremely high cost performance. During the preparation process, the activated carbon cotton felt after treatments, is successfully compounded with the zeolite particles with more excellent sound absorption performance, so that the sound absorption performance is significantly improved and the cost performance is extremely high.

An acoustically driven ferromagnetic resonance (ADFMR) device includes a piezoelectric element, a pair of transducers arranged to activate the piezoelectric element to generate an acoustic wave, a magnetostrictive element arranged to receive the acoustic wave, and a readout circuit to detect one of either a change in the magnetostrictive element or a change in the acoustic wave.

An acoustically driven ferromagnetic resonance (ADFMR) device includes a piezoelectric element, a pair of transducers arranged to activate the piezoelectric element to generate an acoustic wave, a magnetostrictive element arranged to receive the acoustic wave, and a readout circuit to detect one of either a change in the magnetostrictive element or a change in the acoustic wave.

Sound direction detection devices include cylinders or other longitudinally extended structures having rotational symmetry about their longitudinal axes and multiple, rotationally equivalent resonators contained therein. Each resonator contains a microphone or other transducer that is activated when the resonator resonates.

Sound direction detection devices include cylinders or other longitudinally extended structures having rotational symmetry about their longitudinal axes and multiple, rotationally equivalent resonators contained therein. Each resonator contains a microphone or other transducer that is activated when the resonator resonates.

Various techniques for driving phased array systems are described, specifically intended for acoustic phased arrays with applications to mid-air haptics, parametric audio, acoustic levitation and acoustic imaging, including a system: 1) that is capable of mitigating the effect of the changes in the air to provide a consistent haptic experience; 2) that produces trap points in air; 3) that defines phased-array optimization in terms of vectors for the production of more consistent haptic effects; 4) that defines one or more control points or regions in space via a controlled acoustic field; 5) that uses a reduced representation method for the construction of acoustic basis functions; 6) that performs efficient evaluation of complex-valued functions for a large quantity of throughput; 7) that generates a Krylov sub-space of a matrix; and 8) that maximizes an objective described by different control points and/or regions to those used to create the acoustic basis functions.

A beamforming system comprises an input module, a phase-difference module, a delay distribution module, and a delay estimation module configured to make a final delay estimation based on the delay distribution. The final delay estimation is applied to align one of two selected channels and combine the two channels to obtain a signal of interest. The phase-difference module calculates phase differences for a range of frequency bins. The delay estimation module considers all possible delays derived from the phase differences, including multiples of ±2π to overcome the ambiguity in high frequency bins when the spacing between two acoustic sensors is longer than the half of the wavelengths.