Abstract: The present invention provides a hot-pressed carbon/sulfur composite energy-storage cathode utilized in a lithium-sulfur battery, comprising: a conductive porous substrate with specific surface area of 1˜100 m2/g before sulfur loading, and a sulfur layer formed on the conductive porous substrate by hot-pressing method; the cathode has a sulfur loading of 8 mg/cm2 and a sulfur content of 73 wt %. The lithium-sulfur battery of the present invention, with the significant enhancement of the loading and the content of the active material achieved by the hot-pressed carbon/sulfur composite energy-storage cathode, may have the effect of high cyclability and high energy density in a lean-electrolyte lithium-sulfur battery with a low electrolyte-to-sulfur ratio of 7˜4 ?L/mg.

Abstract: A voltage level shifter includes an input transistor, a control circuit, a reset circuit, and a keeper circuit. The input transistor is configured to receive an input voltage and a first reference voltage. The control circuit is configured to generate a pulse voltage according to the input voltage and one of a node voltage, an output voltage, and an inversion input voltage. The reset circuit is configured to receive the first reference voltage and a second reference voltage and controlled by the pulse voltage. The reset circuit is coupled to the input transistor at a first node where the node voltage is generated. The keeper circuit is coupled to the first node and configured to generate the output voltage according to the node voltage, the first reference voltage, the second reference voltage, and the output voltage.

Abstract: A control circuit for a neural network system includes a first multiply accumulate circuit, a first neuron value storage circuit and a first processor. The first multiply accumulate circuit includes n memristive cells. The first terminals of the n memristive cells receive a supply voltage. The second terminals of the n memristive cells are connected with a first bit line. The control terminals of the n memristive cells are respectively connected with n word lines. Moreover, n neuron values of a first layer are stored in the first neuron value storage circuit. In an application phase, the first neuron value storage circuit controls the n word lines according to binary codes of the n neuron values. The first processor generates a first neuron value of a second layer.

Abstract: A control circuit for a neural network system includes a first multiply accumulate circuit, a first neuron value storage circuit and a first processor. The first multiply accumulate circuit includes n memristive cells. The first terminals of the n memristive cells receive a supply voltage. The second terminals of the n memristive cells are connected with a first bit line. The control terminals of the n memristive cells are respectively connected with n word lines. Moreover, n neuron values of a first layer are stored in the first neuron value storage circuit. In an application phase, the first neuron value storage circuit controls the n word lines according to binary codes of the n neuron values. The first processor generates a first neuron value of a second layer.

Abstract: A differential sensing device includes two reference cells, four path selectors, and four sample circuits. The first path selector is coupled to a first sensing node, the second reference cell, and a first memory cell. The second path selector is coupled to a second sensing node, the first reference cell, and the first memory cell. The third path selector is coupled to a third sensing node, the first reference cell, and a second memory cell. The fourth path selector is coupled to a fourth sensing node, the second reference cell, and the second memory cell. During a sample operation, the first sample circuit samples a first cell current, the second sample circuit samples the first reference current, the third sample circuit samples a second cell current, and the fourth sample circuit samples the second reference current.

Abstract: A differential sensing device includes two reference cells, four path selectors, and four sample circuits. The first path selector is coupled to a first sensing node, the second reference cell, and a first memory cell. The second path selector is coupled to a second sensing node, the first reference cell, and the first memory cell. The third path selector is coupled to a third sensing node, the first reference cell, and a second memory cell. The fourth path selector is coupled to a fourth sensing node, the second reference cell, and the second memory cell. During a sample operation, the first sample circuit samples a first cell current, the second sample circuit samples the first reference current, the third sample circuit samples a second cell current, and the fourth sample circuit samples the second reference current.

Abstract: A multiply accumulate circuit receives m one-bit neuron values from a first layer of a neural network system. The multiply accumulate circuit includes m non-volatile memory cells and m current sources. In addition, m current paths are defined by the m non-volatile memory cells and the m current sources collaboratively. A first current path is defined by a first non-volatile memory cell and a first current source. A first terminal of the first current source receives a first supply voltage. A second terminal of the first current source is connected with a first terminal of the first non-volatile memory cell. A second terminal of the first non-volatile memory cell is connected with an output terminal of the multiply accumulate circuit. A control terminal of the first current source receives a first one-bit neuron value.

Abstract: A control circuit for a neural network system includes a first multiply accumulate circuit, a first neuron value storage circuit and a first processor. The first multiply accumulate circuit includes n memristive cells. The first terminals of the n memristive cells receive a supply voltage. The second terminals of the n memristive cells are connected with a first bit line. The control terminals of the n memristive cells are respectively connected with n word lines. Moreover, n neuron values of a first layer are stored in the first neuron value storage circuit. In an application phase, the first neuron value storage circuit controls the n word lines according to binary codes of the n neuron values. The first processor generates a first neuron value of a second layer.

Abstract: A control circuit for a neural network system includes a first multiply accumulate circuit, a first neuron value storage circuit and a first processor. The first multiply accumulate circuit includes n memristive cells. The first terminals of the n memristive cells receive a supply voltage. The second terminals of the n memristive cells are connected with a first bit line. The control terminals of the n memristive cells are respectively connected with n word lines. Moreover, n neuron values of a first layer are stored in the first neuron value storage circuit. In an application phase, the first neuron value storage circuit controls the n word lines according to binary codes of the n neuron values. The first processor generates a first neuron value of a second layer.