CircuitWay vs SPICENet Visualization

CircuitWay is a SPICE simulator of analog and digital circuits. It can easily design, simulate, and analyze electronic circuits on your device. There’re 100 example circuits for your convenience to explore. They range from basic BJT amplifiers, to MOS amplifiers, to oscillators, to filters, to PMICs, to 555 timers, to switched capacitor circuits, to high frequency circuits, to basic digital circuits, and finally 10 complex projects. The 10 complex projects consist of: UART, RISC CPU, PLL, Clock and Data Recovery (CDR), SRAM, R-2R Ladder DAC, Σ-Δ ADC, SAR ADC, FIR Filter, IIR Filter. There’re 106 type of library elements in the CircuitWay, range from resistor, capacitor, inductor, to sin, pulse, pwl voltage source, to controlled source such as: VCVC, VCCS, CCVS, CCCS, to behavior voltage source, to switches, to opamps, to tranformers, to Verilog code, to standard digital cells, to ADC/DAC, to 555 chip, to Arduino and more. Because CircuitWay supports Verilog, so you can build indefinitely any number of digital circuits using Verilog hardware design language. CircuitWay can also support Arduino, so you can use c language to model a large number of complex systems. CircuitWay supports 4 type of analysis: Transient, DC sweep, AC, FFT. You can manipulate and inspect waveforms in the schematic page, and build waveform math expressions to calculate new waveforms from exist waveforms. CircuitWay is serious about helping you to understand more about circuits. If you find and want to report bugs, you can contact dianlutu9988@gmail.com or circuitway@126.com Terms of Use: https://www.apple.com/legal/internet-services/itunes/dev/stdeula/

SpiceNet is an educational and research-oriented simulation app for exploring SPICEnet, a self-organizing neural model for learning relationships between sensory inputs. Run simulations from generated data or import your own CSV file, adjust network and data parameters, and inspect the results through scatter plots, line charts, histograms, tuning curves, and heatmaps. The app also includes a theory section explaining the SPICEnet model and a benchmark tool for comparing standard Swift computation with Apple’s Accelerate framework. Features: - Run SPICEnet simulations from random data - Import CSV files and select columns for analysis - Adjust neurons, learning rate, initialization range, data count, transformation type, and chunk size - Visualize simulation output with multiple chart types - View explanatory SPICEnet theory content - Run local performance benchmarks - Export benchmark results as a PDF All simulations and file processing run locally on the device. Academic context: SpiceNet was developed by Omar Ashour as part of a bachelor thesis under the supervision of Prof. Dr.-Ing. Cristian Axenie at Technische Hochschule Nürnberg Georg Simon Ohm.