JK Flip-Flop Simulator Hold (0,0) Reset (0,1) Set (1,0) Toggle (1,1) Manual Clock Pulse Auto Clock: OFF ⏱ Speed: Q=0 | J=0 K=0 📘 Logic Explanation Select J/K inputs and press clock to trigger the flip-flop. 📜 Steps Log Simulation ready...

Interactive Eye Diagram & Noise Margin Filter Roll-off (α) α = 0.4 Noise Level Bitstream (TX) Stage 1: Components (Click Legend to Hide/Show) Stage 2: Composite Signal Stage 3: The Eye (Annotated Analysis) Simulation Workflow 1. Pulse Mapping: Each bit a[k] is mapped to a pulse shape p(t) . We use the Raised Cosine filter, which is the standard for bandwidth-limited communication. Clicking the legend above removes a specific bit's contribution to show how it affects the neighbors. 2. Linear Superposition: The total signal x(t) is the sum of all individual pulses shifted by the symbol period T . This "Combined Waveform" shows how pulses "bleed" into each other, cre...

BPSK Waveform Decoding using Matched Filter (Convolution) Noise (SNR dB) 5 dB Carrier Frequency 2 cycles/bit Binary Data TX: RX: Stage 1: Noisy BPSK Stream x[n] (Observe Phase Flips) Stage 2: Filter Output y[n] (Convolution Peaks at Yellow Sticks) Simulation Methodology: BPSK Convolution In BPSK, the pulse shape is a sine wave. To decode this optimally, we use a Direct Matched Filter whose impulse response is a time-reversed version of the carrier cycle. 1. The Linear Convolution: The green waveform is generated by sliding the BPSK template across the noisy input stream. Mathematically: y[n] = Σ x[k] · h[n - k] Because the BPSK carrier is perfectly "matched...

Decoding of Pulse-Shaped BPSK Waveform Roll-off Factor (α) 0.5 Timing Jitter (τ) 0% Offset Transmit Bits (a_k) TX: RX: Mathematical Framework In bandwidth-limited channels, we cannot use rectangular pulses because they have infinite spectral width. Instead, we use the Raised Cosine (RC) pulse, defined in the time domain as: p(t) = sinc(t/T) * [ cos(παt/T) / (1 - (2αt/T)^2) ] The total transmitted waveform is the superposition (sum) of these pulses shifted by the symbol period T : x(t) = Σ a_k * p(t - kT) 1. Nyquist's First Criterion: For zero Intersymbol Interference (ISI) , the pulse must satisfy p(0)=1 and p(kT)=0 for all k ≠ 0....

Manchester Encoding (Line Coding) Clock Jitter (%) Noise Level Data String TX: RX: Summary: In Manchester Encoding, the transition occurs at exactly T/2 . A 0-to-1 transition represents a logical '1', and a 1-to-0 transition represents a logical '0'. If the "Yellow Sticks" (Clock) are out of sync with the signal transitions, the receiver will fail to detect the change, causing decoding errors.

PAM-4 Decoding & Timing Jitter Simulator Timing Jitter (Offset) 0% Offset Noise (SNR dB) 25 dB Data (Bit Pairs) DECODED SYMBOLS (2 BITS PER DURATION) Summary: In PAM-4, the receiver uses 3 thresholds to distinguish between 4 levels. If Timing Jitter is high, the "Yellow Sticks" move away from the stable center of the pulse, causing the receiver to sample the "Transition Edge" instead of the "Pulse Peak," leading to errors.

Signal Fidelity SYSTEM FIDELITY 100% High Fidelity (Faithful Reproduction) Phase Error (Deg) Noise Level (SNR) Fidelity measures how accurately the Output (Green) matches the Input (Dashed Gray). In communication systems, two things destroy fidelity: Phase Shift: If the receiver is out of sync, the signal strength drops. At 90°, fidelity is 0% because the wave vanishes. Noise: Random interference adds "jitter" to the wave, making it an unfaithful copy of the original.

Analog Demodulation Simulator (DSB-SC / SSB-SC / AM) Analog Demodulation Simulator (DSB-SC / SSB-SC / AM) Scheme DSB-SC SSB-SC (USB) Standard AM SNR (dB) 30 dB Phase Error (Deg) 0° System: DSB-SC Fidelity: 100% Modulated Wave (Transmitted) Demodulated vs Original (Comparison) Simulator Methodology DSB-SC: Formed by m(t) * cos(ωc t) . Since the carrier is suppressed, we must multiply by a local carrier at the receiver. If the Phase Error is 90°, the signal vanishes entirely. SSB-SC: Transmits only one sideband. It is more spectrum efficient but requires complex Hilbert transform processing. Mathematically: m(t)...